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’))
Cleaning the argument list before passing it to the constructor is probably the best way to go about it. I’d advice against writing your own __init__ function though, since the dataclass’ __init__ does a couple of other convenient things that you’ll lose by overriding it. Also, since the argument-cleaning logic is very tightly bound to … Read more
The way dataclasses combines attributes prevents you from being able to use attributes with defaults in a base class and then use attributes without a default (positional attributes) in a subclass. That’s because the attributes are combined by starting from the bottom of the MRO, and building up an ordered list of the attributes in … Read more
Instead of checking for type equality, you should use isinstance. But you cannot use a parametrized generic type (typing.List[int]) to do so, you must use the “generic” version (typing.List). So you will be able to check for the container type but not the contained types. Parametrized generic types define an __origin__ attribute that you can … Read more
Data classes are just regular classes that are geared towards storing state, rather than containing a lot of logic. Every time you create a class that mostly consists of attributes, you make a data class. What the dataclasses module does is to make it easier to create data classes. It takes care of a lot … Read more