I have a dataclass object that has nested dataclass objects in it. However, when I create the main object, the nested objects turn into a dictionary:
@dataclass
class One:
f_one: int
f_two: str
@dataclass
class Two:
f_three: str
f_four: One
Two(**{'f_three': 'three', 'f_four': {'f_one': 1, 'f_two': 'two'}})
Two(f_three='three', f_four={'f_one': 1, 'f_two': 'two'})
obj = {'f_three': 'three', 'f_four': One(**{'f_one': 1, 'f_two': 'two'})}
Two(**obj)
Two(f_three='three', f_four=One(f_one=1, f_two='two'))
As you can see only **obj
works.
Ideally I'd like to construct my object to get something like this:
Two(f_three='three', f_four=One(f_one=1, f_two='two'))
Is there any way to achieve that other than manually converting nested dictionaries to corresponding dataclass object, whenever accessing object attributes?
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__
.