I'd like to use pydantic for handling data (bidirectionally) between an api and datastore due to it's nice support for several types I care about that are not natively json-serializable. It has better read/validation support than the current approach, but I also need to create json-serializable dict objects to write out. from uuid import UUID, uuid4 from pydantic import BaseModel class Model(BaseModel): the_id: UUID instance = Model(the_id=uuid4()) print("1: %s" % instance.dict() print("2: %s" % instance.json() prints {'the_id': UUID('4108356a-556e-484b-9447-07b56a664763')} >>> inst.json() '{"the_id": "4108356a-556e-484b-9447-07b56a664763"}' Id like the following: {"the_id": "4108356a-556e-484b-9447-07b56a664763"} # eg "json-compatible" dict It appears that while pydantic has all the mappings, but I can't find any usage of the serialization outside the standard json ~recursive encoder (json.dumps( ... default=pydantic_encoder)) in pydantic/main.py. but I'd prefer to keep to one library for both validate raw->obj (pydantic is great at this) as well as the obj->raw(dict) so that I don't have to manage multiple serialization mappings. I suppose I could implement something similar to the json usage of the encoder, but this should be a common use case? Other approaches such as dataclasses(builtin) + libraries such as dataclasses_jsonschema provide this ~serialization to json-ready dict, but again, hoping to use pydantic for the more robust input validation while keeping things symmetrical. Continue reading...
