Question

我想为数据类创建字典，该字典包含作为属性的数据类列表

以下是我要实现的目标的一个示例：

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

我发现的最近的装饰器是这个装饰器，但是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可以完成此装饰的装饰器？（我在建筑装饰方面的经验为零）

非常感谢任何注释/代码。谢谢

Answer 1

pip install validated-dc

ValidatedDC：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 2

这没有提供如何更改装饰器的信息，如果您不希望使用任何第三方包装，请忽略此答案。但我认为pydantic可以为您做点什么想。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

如果您实际上想直接从key21访问key2，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使装饰器工作，请再次忽略此操作。否则，安装pydantic不会造成伤害：）

Answer 3

好的，因此我对装饰器进行了一些更改，但是它非常特定于此处提供的示例。主要问题是您的List[level2]字段不是dataclass。因此，为了解决这个问题，我玩了一会儿，发现有一个 args 属性可以告诉您列表中的嵌套类型。我以前从未使用过数据类（除了pydantic以外），所以也许在那里会有更好的答案

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)])])

Python中数据类嵌套列表的装饰器

3 个答案: