Compatibility between outputs of skrub.datasets.fetch_X and sklearn.datasets.fetch_X

[baggiponte]

Currently, sklearn datasets return a sklearn.utils._bunch.Bunch with the following attributes: ['DESCR', 'data', 'feature_names', 'frame', 'target', 'target_names']. skrub data objects return a skrub.datasets._fetching.DatasetAll instead with the following attributes:

['X',
 '__annotations__',
 '__class__',
 '__dataclass_fields__',
 '__dataclass_params__',
 '__delattr__',
 '__dict__',
 '__dir__',
 '__doc__',
 '__eq__',
 '__format__',
 '__ge__',
 '__getattribute__',
 '__gt__',
 '__hash__',
 '__init__',
 '__init_subclass__',
 '__le__',
 '__lt__',
 '__match_args__',
 '__module__',
 '__ne__',
 '__new__',
 '__reduce__',
 '__reduce_ex__',
 '__repr__',
 '__setattr__',
 '__sizeof__',
 '__str__',
 '__subclasshook__',
 '__weakref__',
 'description',
 'name',
 'path',
 'read_csv_kwargs',
 'source',
 'target',
 'y']

(huge fan of dataclasses by the way)

This works fine but I was wondering if you wanted to be consistent with the sklearn API. The biggest con is that it might be a bit tedious to rewrite stuff. But if you inherit from the Bunch object you'd have less stuff to maintain too, I guess?