It's not possible to use a dataclass to make an attribute that sometimes exists and sometimes doesn't because the generated __init__, __eq__, __repr__, etc hard-code which attributes they check.

However, it is possible to make a dataclass with an optional argument that uses a default value for an attribute (when it's not provided).

from dataclasses import dataclass
from typing import Optional

@dataclass
class CampingEquipment:
    knife: bool
    fork: bool
    missing_flask_size: Optional[int] = None
    
kennys_stuff = {
    'knife':True,
    'fork': True
}

print(CampingEquipment(**kennys_stuff))

And it's possible to make a dataclass with an argument that's accepted to __init__ but isn't an actual field. So you could do something like this:

from dataclasses import dataclass, InitVar
from typing import Optional

@dataclass
class CampingEquipment:
    knife: bool
    fork: bool
    missing_flask_size: InitVar[Optional[int]] = None

    def __post_init__(self, missing_flask_size):
        if missing_flask_size is not None:
            self.missing_flask_size = missing_flask_size

If you really want classes to either to have that attribute present or not have it at all, you could subclass your dataclass and make a factory function that creates one class or the other based on whether that missing_flask_size attribute is present:

from dataclasses import dataclass

@dataclass
class CampingEquipment:
    knife: bool
    fork: bool


@dataclass
class CampingEquipmentWithFlask(CampingEquipment):
    missing_flask_size: int


def equipment(**fields):
    if 'missing_flask_size' in fields:
        return CampingEquipmentWithFlask(**fields)
    return CampingEquipment(**fields)
    

kennys_stuff = {
    'knife':True,
    'fork': True
}

print(equipment(**kennys_stuff))

If you really wanted to (I wouldn't recommend it though), you could even customize the __new__ of CampingEquipment to return an instance of that special subclass when that missing_flask_size argument is given (though then you'd need to set init=False and make your own __init__ as well on that class).

The underlying problem that you have seems to be the same one that is described here. The short version of that post is that in a function signature (including the dataclass-generated __init__ method), obligatory arguments (like NamedEvent's name) can not follow after arguments with default values (which are necessary to define the behavior of Event's updated_at) - a child's fields will always follow after those of its parent.

So either you have no default values in your parent class (which doesn't work in this case) or all your child's fields need default values (which is annoying, and sometimes simply not feasible).

The post I linked above discusses some patterns that you can apply to solve your problem, but as a nicer alternative you can also use the third part party package pydantic which already solved this problem for you. A sample implementation could look like this:

import pydantic
from datetime import datetime


class Event(pydantic.BaseModel):
    id: str
    created_at: datetime = None
    updated_at: datetime = None

    @pydantic.validator('created_at', pre=True, always=True)
    def default_created(cls, v):
        return v or datetime.now()

    @pydantic.validator('updated_at', pre=True, always=True)
    def default_modified(cls, v, values):
        return v or values['created_at']


class NamedEvent(Event):
    name: str

The default-value specification through validators is a bit cumbersome, but overall it's a very useful package that fixes lots of the shortcomings that you run into when using dataclasses, plus some more.

Using the class definition, an instance of NamedEvent can be created like this:

>>> NamedEvent(id='1', name='foo')
NamedEvent(id='1', created_at=datetime.datetime(2020, 5, 2, 18, 50, 12, 902732), updated_at=datetime.datetime(2020, 5, 2, 18, 50, 12, 902732), name='foo')

You can have an optional parameter in data class by setting a default value, for example an empty string "" or None.

from dataclasses import dataclass
from typings import Optional


@dataclass
class SubOrder:
    n: Optional[int] = None
    name: str = ""