I'm in the process of converting existing dataclasses in my project to pydantic-dataclasses, I'm using these dataclasses to represent models I need to both encode-to and parse-from json. Here's an example of my current approach that is not good enough for my use case, I have a class A that I want to both convert into a dict (to later be converted written as json) and to read from that dict. But the only way I can find to parse the json back into a model gives me back the underlying BaseModel and not the dataclass. note that I'm using the asdict function to convert the dataclass to a dict as it's what the pydantic_encoder uses to convert the dataclass to json, and using the pydantic_encoder what the documentation recommends to convert a pydantic-dataclass to json: https://pydantic-docs.helpmanual.io/usage/dataclasses/ from dataclasses import asdict from pydantic.dataclasses import dataclass from pydantic import BaseModel @dataclass class A: x: str a = A("string") a_dict = asdict(a) parsed_a = A.__pydantic_model__.parse_obj(a_dict) print(f"type of a: {type(a)}") print(f"type of parsed_a: {type(parsed_a)}") print(f"a is instance of A: {isinstance(a, A)}") print(f"parsed_a is instance of A: {isinstance(parsed_a, A)}") print(f"a is instance of BaseModel: {isinstance(a, BaseModel)}") print(f"parsed_a is instance of BaseModel: {isinstance(parsed_a, BaseModel)}") output: type of a: <class '__main__.A'> type of parsed_a: <class '__main__.A'> a is instance of A: True parsed_a is instance of A: False a is instance of BaseModel: False parsed_a is instance of BaseModel: True Is there maybe a way to initialize A from the parsed BaseModel? Continue reading...
