Creating nested dataclass objects in Python

This is a request that is as complex as the dataclasses module itself, which means that probably the best way to achieve this "nested fields" capability is to define a new decorator, akin to @dataclass.

Fortunately, if you don't need the signature of the __init__ method to reflect the fields and their defaults, like the classes rendered by calling dataclass, this can be a whole lot simpler: A class decorator that will call the original dataclass and wrap some functionality over its generated __init__ method can do it with a plain "...(*args, **kwargs):" style function.

In other words, all one needs to do is write a wrapper around the generated __init__ method that will inspect the parameters passed in "kwargs", check if any corresponds to a "dataclass field type", and if so, generate the nested object prior to calling the original __init__. Maybe this is harder to spell out in English than in Python:

from dataclasses import dataclass, is_dataclass

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

Note that besides not worrying about __init__ signature, this also ignores passing init=False - since it would be meaningless anyway.

(The if in the return line is responsible for this to work either being called with named parameters or directly as a decorator, like dataclass itself)

And on the interactive prompt:

In [85]: @dataclass
    ...: class A:
    ...:     b: int = 0
    ...:     c: str = ""
    ...:         

In [86]: @dataclass
    ...: class A:
    ...:     one: int = 0
    ...:     two: str = ""
    ...:     
    ...:         

In [87]: @nested_dataclass
    ...: class B:
    ...:     three: A
    ...:     four: str
    ...:     

In [88]: @nested_dataclass
    ...: class C:
    ...:     five: B
    ...:     six: str
    ...:     
    ...:     

In [89]: obj = C(five={"three":{"one": 23, "two":"narf"}, "four": "zort"}, six="fnord")

In [90]: obj.five.three.two
Out[90]: 'narf'

If you want the signature to be kept, I'd recommend using the private helper functions in the dataclasses module itself, to create a new __init__.

You can use post_init for this

from dataclasses import dataclass
@dataclass
class One:
    f_one: int
    f_two: str

@dataclass
class Two:
    f_three: str
    f_four: One
    def __post_init__(self):
        self.f_four = One(**self.f_four)

data = {'f_three': 'three', 'f_four': {'f_one': 1, 'f_two': 'two'}}

print(Two(**data))
# Two(f_three='three', f_four=One(f_one=1, f_two='two'))