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)

如果你使用的是Python 3.5+，你可以使用json来序列化和反序列化到普通的旧Python对象:

import jsons

response = request.POST

# You'll need your class attributes to match your dict keys, so in your case do:
response['id'] = response.pop('user_id')

# Then you can load that dict into your class:
user = jsons.load(response, FbApiUser)

user.save()

你也可以让FbApiUser从jsons继承。JsonSerializable更优雅:

user = FbApiUser.from_json(response)

如果你的类由Python默认类型组成，比如字符串、整数、列表、日期时间等，这些例子就可以工作。不过，jsons lib需要自定义类型的类型提示。

def load_model_from_dict(self, data: dict):
    for key, value in data.items():
        self.__dict__[key] = value
    return self

它帮助返回你自己的模型，从字典中不可预见的变量。

在寻找解决方案时，我偶然发现了这个博客:https://blog.mosthege.net/2016/11/12/json-deserialization-of-nested-objects/

它使用与前面回答中相同的技术，但使用了装饰器。 我发现另一件有用的事情是，它在反序列化结束时返回一个类型化对象

class JsonConvert(object):
    class_mappings = {}

    @classmethod
    def class_mapper(cls, d):
        for keys, cls in clsself.mappings.items():
            if keys.issuperset(d.keys()):   # are all required arguments present?
                return cls(**d)
        else:
            # Raise exception instead of silently returning None
            raise ValueError('Unable to find a matching class for object: {!s}'.format(d))

    @classmethod
    def complex_handler(cls, Obj):
        if hasattr(Obj, '__dict__'):
            return Obj.__dict__
        else:
            raise TypeError('Object of type %s with value of %s is not JSON serializable' % (type(Obj), repr(Obj)))

    @classmethod
    def register(cls, claz):
        clsself.mappings[frozenset(tuple([attr for attr,val in cls().__dict__.items()]))] = cls
        return cls

    @classmethod
    def to_json(cls, obj):
        return json.dumps(obj.__dict__, default=cls.complex_handler, indent=4)

    @classmethod
    def from_json(cls, json_str):
        return json.loads(json_str, object_hook=cls.class_mapper)

用法:

@JsonConvert.register
class Employee(object):
    def __init__(self, Name:int=None, Age:int=None):
        self.Name = Name
        self.Age = Age
        return

@JsonConvert.register
class Company(object):
    def __init__(self, Name:str="", Employees:[Employee]=None):
        self.Name = Name
        self.Employees = [] if Employees is None else Employees
        return

company = Company("Contonso")
company.Employees.append(Employee("Werner", 38))
company.Employees.append(Employee("Mary"))

as_json = JsonConvert.to_json(company)
from_json = JsonConvert.from_json(as_json)
as_json_from_json = JsonConvert.to_json(from_json)

assert(as_json_from_json == as_json)

print(as_json_from_json)

数据类向导是一种现代的选项，可以类似地为您工作。它支持自动键大小写转换，如camelCase或TitleCase，这两者在API响应中都很常见。

当将实例转储到dict/JSON时，默认的键转换是camelCase，但这可以很容易地使用主数据类上提供的Meta配置来覆盖。

https://pypi.org/project/dataclass-wizard/

from dataclasses import dataclass

from dataclass_wizard import fromdict, asdict


@dataclass
class User:
    name: str
    age: int
    is_active: bool


data = {
    'name': 'John',
    'age': 30,
    'isActive': True,
}

user = fromdict(User, data)
assert user == User(name='John', age=30, is_active=True)

json_dict = asdict(user)
assert json_dict == {'name': 'John', 'age': 30, 'isActive': True}

设置元配置的例子，当序列化为dict/JSON时，将字段转换为lisp-case:

DumpMeta(key_transform='LISP').bind_to(User)

Dacite也可能是您的解决方案，它支持以下功能:

嵌套结构 (基本)类型检查 可选字段(即typing.Optional) 工会 向前引用 集合 自定义类型钩子

https://pypi.org/project/dacite/

from dataclasses import dataclass
from dacite import from_dict


@dataclass
class User:
    name: str
    age: int
    is_active: bool


data = {
    'name': 'John',
    'age': 30,
    'is_active': True,
}

user = from_dict(data_class=User, data=data)

assert user == User(name='John', age=30, is_active=True)