I just joined the ideas list today so I do not know if this has been discussed.

Using dataclasses has been great for me, but a challenge is what to do when you don't know if the object you are using is a dataclass, and could be a variety of other classes.

This could easily occur when you don't want to assume the data type being used by the user to represent their data, but wish to turn it into a dict (if an API exists to do so).

d = asdict(obj) if is_dataclass(obj) else dict_factory(obj)

If it could also be a namedtuple, you might write this:

d = asdict(obj) if is_dataclass(obj) else obj._asdict() if isinstance(obj, namedtuple) else dict_factory(obj)

and if it could also be some other object with an .asdict() method:

d = asdict(obj) if is_dataclass(obj) else obj._asdict() if isinstance(obj, namedtuple) else obj.asdict() if hasattr(obj, "asdict") else dict_factory(obj) 

This gets pretty silly/unwieldy somewhat quickly.
The idea is: 1. identifying the various "asdict" APIs used in the standard library, and 2. include a keyword option for dataclasses.asdict() to cast a non-dataclasses object to a dict using these protocols (and falling back on factory_dict(obj) if it is provided).