For my PyCon 2025 talk I did this. Video isn't up yet, but slides are here: https://pythonspeed.com/pycon2025/slides/

The linked-from-original-article ijson article was the inspiration for the talk: https://pythonspeed.com/articles/json-memory-streaming/

You can't add extra attributes that weren't part of the original dataclass definition:

  >>> from dataclasses import dataclass
  >>> @dataclass
  ... class C: pass
  ... 
  >>> C().x = 1
  >>> @dataclass(slots=True)
  ... class D: pass
  ... 
  >>> D().x = 1
  Traceback (most recent call last):
    File "<python-input-4>", line 1, in <module>
      D().x = 1
      ^^^^^
  AttributeError: 'D' object has no attribute 'x' and no __dict__ for setting new attributes

Most of the time this is not a thing you actually need to do.

You probably want to use Discriminated Unions https://docs.pydantic.dev/latest/concepts/unions/#discrimina...

The only reason I can think of for the behavior you are describing is if one of the unioned types at some level of the hierarchy is equivalent to Dict[str, Any]. My understanding is that Pydantic will explore every option provided recursively and raise a ValidationError if none match but will never just give up and hand you a partially validated object.

Are you able to share a snippet that reproduces what you're seeing?

At some point, we have to admit we're asking too much from our tools.

I know nothing about your context, but in what context would a single model need to support so many permutations of a data structure? Just because software can, doesn't mean it should.

msgspec is much more memory efficient out of the box, yes. Also quite fast.

A great feature of pydantic are the validation hooks that let you intercept serialization/deserialization of specific fields and augment behavior.

For example if you are querying a DB that returns a column as a JSON string, trivial with Pydantic to json parse the column are part of deser with an annotation.

Pydantic is definitely slower and not a 'zero cost abstraction', but you do get a lot for it.

Once you switch to ijson it will not save any memory, no, because ijson essentially uses zero memory for the parsing. You're just left with the in-memory representation.