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Comment by goodoldneon | Hacker News Reader

Dataclasses are nice but they have a big downside: extending a dataclass with a default property can raise an error.

If you run this code:

    import dataclasses

    @dataclasses.dataclass
    class Base:
        a: int
        b: int = 1

    @dataclasses.dataclass
    class Child(Base):
        c: int

Then you'll get this error:

  TypeError: non-default argument 'c' follows default argument

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that's because you are expecting dataclasses to create a default `__init__()` for you, which it can't do with that declaration. set init=False if you don't want it to do that.

    import dataclasses

    @dataclasses.dataclass
    class Base:
        a: int
        b: int = 1

    @dataclasses.dataclass(init=False)
    class Child(Base):
        c: int

if you want the init to be generated for you, you have to tell it how, given that "b" has a default value. so "c" needs to be keyword only here:

    import dataclasses

    @dataclasses.dataclass
    class Base:
        a: int
        b: int = 1

    @dataclasses.dataclass
    class Child(Base):
        _: dataclasses.KW_ONLY
        c: int

Looks like that works but it’s unintuitive. Pydantic can handle this situation without the weird KW_ONLY thing, so dataclasses should too

hm it implicitly decides to be KW_ONLY? OK

does not work:

    from pydantic import dataclasses

    @dataclasses.dataclass
    class Base:
        a: int
        b: int = 1

    @dataclasses.dataclass
    class Child(Base):
        c: int

error

    File "pydantic/dataclasses.py", line 265, in pydantic.dataclasses.dataclass
    ...      
    File "/opt/python-3.10.0/lib/python3.10/dataclasses.py", line 539, in _init_fn
      raise TypeError(f'non-default argument {f.name!r} '
   TypeError: non-default argument 'c' follows default argument

it works with KW_ONLY though awkward that pydantic.dataclasses doesn't supply it directly, need to split up imports among pydantic.dataclasses and dataclasses.

Extend from pydantic.BaseModel instead of using the dataclasses decorator

not SQLAlchemy compatible, interest lost :)

I didn’t mean “always use Pydantic instead of dataclasses”. I meant “dataclasses have a default property problem but it’s solvable since Pydantic handles them well”

I personally just use `dataclass(kw_only=True)`, which should really be the default in most cases anyways.

I think the same.

`slots=True` should also be the default.

Nice, I think kw_only=True and slots=True solve a lot of my dataclass problems. Wish they defaulted to true

> Nice, I think kw_only=True and slots=True solve a lot of my dataclass problems. Wish they defaulted to true

While it doesn’t solve reading other people’s code with the defaults you’d like to have, dataclass being a decorator and not a special syntax means that you can just derive a new decorator from it with the defaults you want.

> you can just derive a new decorator from it with the defaults you want.

This could hurt basic static analysis.

> This could hurt basic static analysis.

That’s a good point. I know some of the python static analysis tools can “see through” some simple indirection, but don't know if even a simple wrapper injecting arguments would work with any (or which) of them for this purpose.

It's ugly but you can fix this with `dataclass_transform`

`frozen=True` is really nice also if your data does not change :)

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