Python中数据类嵌套列表的装饰器

Question

我想为一个数据类创建一个字典，其中包含作为属性的数据类列表

这是我想要实现的示例：

from typing import List
from dataclasses import dataclass


@dataclass
class level2:
    key21: int
    key22: int


@nested_dataclass
class level1:
    key1: int
    key2: List[level2]


data = {
    'key1': value1,
    'key2': [{
        'key21': value21,
        'key22': value22,
    }]
}

my_object = level1(**data)
print(my_object.key2[0].key21) #should print value21

我发现最近的装饰器是这个，但它不适用于数据类列表： Creating nested dataclass objects in Python

def is_dataclass(obj):
    """Returns True if obj is a dataclass or an instance of a
    dataclass."""
    _FIELDS = '__dataclass_fields__'
    return hasattr(obj, _FIELDS)


def nested_dataclass(*args, **kwargs):

    def wrapper(cls):
        cls = dataclass(cls, **kwargs)
        original_init = cls.__init__

        def __init__(self, *args, **kwargs):
            for name, value in kwargs.items():
                field_type = cls.__annotations__.get(name, None)

                if is_dataclass(field_type) and isinstance(value, dict):
                     new_obj = field_type(**value)
                     kwargs[name] = new_obj

            original_init(self, *args, **kwargs)

        cls.__init__ = __init__
        return cls

    return wrapper(args[0]) if args else wrapper

您将如何修改此装饰器或创建一个可以完成这项工作的装饰器？ （我在建筑装饰师方面的经验为零）

非常感谢任何评论/代码。谢谢

Answer 1

好的，所以我稍微更改了装饰器，但它对此处提供的示例非常具体。主要问题是您的List[level2] 字段不是dataclass。所以为了解决这个问题，我玩了一下，发现有一个 args 属性可以告诉你列表中的嵌套类型。我以前从未使用过数据类（pydantic 除外），所以也许有更好的答案

def nested_dataclass(*args, **kwargs):

    def wrapper(cls):
        cls = dataclass(cls, **kwargs)
        original_init = cls.__init__

        def __init__(self, *args, **kwargs):
            for name, value in kwargs.items():
                field_type = cls.__annotations__.get(name, None)

                if hasattr(field_type, '__args__'):
                    inner_type = field_type.__args__[0]
                    if is_dataclass(inner_type):
                        new_obj = [inner_type(**dict_) for dict_ in value]
                        kwargs[name] = new_obj

            original_init(self, *args, **kwargs)

        cls.__init__ = __init__
        return cls

    return wrapper(args[0]) if args else wrapper


@dataclass
class level2:
    key21: int
    key22: int

@nested_dataclass
class level1:
    key1: int
    key2: List[level2]


data = {
    'key1': 1,
    'key2': [{
        'key21': 21,
        'key22': 22,
    },
    {
     'key21': 23,
     'key22': 24
     }]
}

my_object = level1(**data)
print(my_object.key2[0].key21) #should print 21
print(my_object.key2[1].key21) #should print 23

@nested_dataclass
class random:
    key1: int
    key2: List[int]

random_object = random(**{'key1': 1, 'key2': [1,2,3]})
print(random_object.key2) # prints [1,2,3]

进一步嵌套

@nested_dataclass
class level3:
    key3: List[level1]

level3(**{'key3': [data]})

输出：

level3(key3=[level1(key1=1, key2=[level2(key21=21, key22=22), level2(key21=23, key22=24)])])

Answer 2

pip install 验证-dc

验证DC：https://github.com/EvgeniyBurdin/validated_dc

from dataclasses import dataclass
from typing import List, Union

from validated_dc import ValidatedDC


@dataclass
class Level2(ValidatedDC):
    key21: int
    key22: int


@dataclass
class Level1(ValidatedDC):
    key1: int
    key2: List[Level2]


data = {
    'key1': 1,
    'key2': [{
        'key21': 21,
        'key22': 22,
    }]
}

my_object = Level1(**data)
assert my_object.key2[0].key21 == 21


# ----------------------------------

@dataclass
class Level1(ValidatedDC):
    key1: int
    key2: Union[Level2, List[Level2]]


my_object = Level1(**data)  # key2 - list
assert my_object.key2[0].key21 == 21

data['key2'] = {
    'key21': 21,
    'key22': 22,
}

my_object = Level1(**data)  # key2 - dict
assert my_object.key2.key21 == 21

Answer 3

这不提供如何更改装饰器，如果您不想使用任何 3rd 方包，请忽略此答案。但我认为 pydantic 可以做你想做的事。我建议的唯一原因是因为它不允许您在将 key2 声明为列表时错误地将其作为字典。

from typing import List
from pydantic import BaseModel
class level2(BaseModel):
    key21: int
    key22: int

class level1(BaseModel):
    key1: int
    key2: List[level2]

data = {
    'key1': 1,
    'key2': [{
        'key21': 21,
        'key22': 22,
    }]
}

my_object = level1(**data)
print(my_object.key2[0].key21) # prints 21

如果你真的想直接从key2 访问key21 那么

class level1(BaseModel):
    key1: int
    key2: level2 # Not a list

data = {
    'key1': 1,
    'key2': {
        'key21': 21,
        'key22': 22,
    }
}

my_object = level1(**data)
print(my_object.key2.key21) # prints 21

如果您的目标是成功让装饰器工作，请再次忽略这一点。否则安装 pydantic 不会受到伤害:)