python3 dataclass with **kwargs(asterisk)

Question

Currently I used DTO(Data Transfer Object) like this.

class Test1:
    def __init__(self, 
        user_id: int = None,
        body: str = None):
        self.user_id = user_id
        self.body = body

Example code is very small, But when object scale growing up, I have to define every variable.

While digging into it, found that python 3.7 supported dataclass

Below code is DTO used dataclass.

from dataclasses import dataclass


@dataclass
class Test2:
    user_id: int
    body: str

In this case, How can I allow pass more argument that does not define into class Test2?

If I used Test1, it is easy. Just add **kwargs(asterisk) into __init__

class Test1:
    def __init__(self, 
        user_id: int = None,
        body: str = None,
        **kwargs):
        self.user_id = user_id
        self.body = body

But using dataclass, Can't found any way to implement it.

Is there any solution here?

Thanks.

---

EDIT

class Test1:
    def __init__(self,
        user_id: str = None, 
        body: str = None):
        self.user_id = user_id
        self.body = body

if __name__ == '__main__':
    temp = {'user_id': 'hide', 'body': 'body test'}
    t1 = Test1(**temp)
    print(t1.__dict__)

Result : {'user_id': 'hide', 'body': 'body test'}

As you know, I want to insert data with dictionary type -> **temp

Reason to using asterisk in dataclass is the same.

I have to pass dictinary type to class init.

Any idea here?

Answer 1

The basic use case for dataclasses is to provide a container that maps arguments to attributes. If you have unknown arguments, you can't know the respective attributes during class creation.

You can work around it if you know during initialization which arguments are unknown by sending them to a catch-all attribute by hand:

from dataclasses import dataclass, field


@dataclass
class Container:
    user_id: int
    body: str
    meta: field(default_factory=dict)


# usage:
obligatory_args = {'user_id': 1, 'body': 'foo'}
other_args = {'bar': 'baz', 'amount': 10}
c = Container(**obligatory_args, meta=other_args)
print(c.meta['bar'])  # prints: 'baz'

But in this case you'll still have a dictionary you need to look into and can't access the arguments by their name, i.e. c.bar doesn't work.

---

If you care about accessing attributes by name, or if you can't distinguish between known and unknown arguments during initialisation, then your last resort without rewriting __init__ (which pretty much defeats the purpose of using dataclasses in the first place) is writing a @classmethod:

from dataclasses import dataclass
from inspect import signature


@dataclass
class Container:
    user_id: int
    body: str

    @classmethod
    def from_kwargs(cls, **kwargs):
        # fetch the constructor's signature
        cls_fields = {field for field in signature(cls).parameters}

        # split the kwargs into native ones and new ones
        native_args, new_args = {}, {}
        for name, val in kwargs.items():
            if name in cls_fields:
                native_args[name] = val
            else:
                new_args[name] = val

        # use the native ones to create the class ...
        ret = cls(**native_args)

        # ... and add the new ones by hand
        for new_name, new_val in new_args.items():
            setattr(ret, new_name, new_val)
        return ret

Usage:

params = {'user_id': 1, 'body': 'foo', 'bar': 'baz', 'amount': 10}
Container(**params)  # still doesn't work, raises a TypeError 
c = Container.from_kwargs(**params)
print(c.bar)  # prints: 'baz'

Answer 2

Dataclass only relies on the __init__ method so you're free to alter your class in the __new__ method.

from dataclasses import dataclass


@dataclass
class Container:
    user_id: int
    body: str

    def __new__(cls, *args, **kwargs):
        try:
            initializer = cls.__initializer
        except AttributeError:
            # Store the original init on the class in a different place
            cls.__initializer = initializer = cls.__init__
            # replace init with something harmless
            cls.__init__ = lambda *a, **k: None

        # code from adapted from Arne
        added_args = {}
        for name in list(kwargs.keys()):
            if name not in cls.__annotations__:
                added_args[name] = kwargs.pop(name)

        ret = object.__new__(cls)
        initializer(ret, **kwargs)
        # ... and add the new ones by hand
        for new_name, new_val in added_args.items():
            setattr(ret, new_name, new_val)

        return ret


if __name__ == "__main__":
    params = {'user_id': 1, 'body': 'foo', 'bar': 'baz', 'amount': 10}
    c = Container(**params)
    print(c.bar)  # prints: 'baz'
    print(c.body)  # prints: 'baz'`

Answer 3

Here's a neat variation on this I used.

from dataclasses import dataclass, field
from typing import Optional, Dict


@dataclass
class MyDataclass:
    data1: Optional[str] = None
    data2: Optional[Dict] = None
    data3: Optional[Dict] = None

    kwargs: field(default_factory=dict) = None

    def __post_init__(self):
        [setattr(self, k, v) for k, v in self.kwargs.items()]

This works as below:

>>> data = MyDataclass(data1="data1", kwargs={"test": 1, "test2": 2})
>>> data.test
1
>>> data.test2
2

However note that the dataclass does not seem to know that is has these new attributes:

>>> from dataclasses import asdict
>>> asdict(data)
{'data1': 'data1', 'data2': None, 'data3': None, 'kwargs': {'test': 1, 'test2': 2}}

This means that the keys have to be known. This worked for my use case and possibly others.

Answer 4

from dataclasses import make_dataclass
Clas = make_dataclass('A', 
                      ['d'], 
                      namespace={
                                 '__post_init__': lambda self: self.__dict__.update(self.d)
                      })
d = {'a':1, 'b': 2}
instance = Clas(d)
instance.a

Answer 5

Variation of answer from Trian Svinit:

You could use the following approach:

1. Extra attributes are added via a kwargs argument as such: MyDataclass(xx, yy, kwargs={...})
2. kwargs is a dataclasses.InitVar that is then processed in the __post_init__ of your dataclass
3. You can access all the values with instance.__dict__ (because asdict would not detect the attributes added via kwargs=...

This would only use native features from dataclasses and inheriting this class would still work.

from dataclasses import InitVar, asdict, dataclass
from typing import Dict, Optional


@dataclass
class MyDataclass:
    data1: Optional[str] = None
    data2: Optional[Dict] = None
    data3: Optional[Dict] = None

    kwargs: InitVar[Optional[Dict[str, Any]]] = None

    def __post_init__(self, kwargs: Optional[Dict[str, Any]]) -> None:
        if kwargs:
            for k, v in kwargs.items():
                setattr(self, k, v)


data = MyDataclass(data1="data_nb_1", kwargs={"test1": 1, "test2": 2})
print(data, "-", data.data1, "-", data.test1)
# MyDataclass(data1='data_nb_1', data2=None, data3=None) - data1 - 1
print(asdict(data))
# {'data1': 'data_nb_1', 'data2': None, 'data3': None}
print(data.__dict__)
# {'data1': 'data_nb_1', 'data2': None, 'data3': None, 'test1': 1, 'test2': 2}

---

If you really need to use asdict to get the attributes passed as kwargs, you could start to use private attributes in dataclasses to hack asdict:

from dataclasses import _FIELD, _FIELDSInitVar, asdict, dataclass, field
from typing import Dict, Optional


@dataclass
class MyDataclass:
    data1: Optional[str] = None
    data2: Optional[Dict] = None
    data3: Optional[Dict] = None

    kwargs: InitVar[Optional[Dict[str, Any]]] = None

    def __post_init__(self, kwargs: Optional[Dict[str, Any]]) -> None:
        if kwargs:
            for k, v in kwargs.items():
                setattr(self, k, v)
                self._add_to_asdict(k)

    def _add_to_asdict(self, attr:str) -> None:
        """Add an attribute to the list of keys returned by asdict"""
        f = field(repr=True)
        f.name = attr
        f._field_type = _FIELD
        getattr(self, _FIELDS)[attr] = f

data = MyDataclass(data1="data_nb_1", kwargs={"test1": 1, "test2": 2})
print(asdict(data))
# {'data1': 'data_nb_1', 'data2': None, 'data3': None, 'test1': 1, 'test2': 2}