Use Pydantic to dynamically create specific implementations of an ABC based on input data

pydantic_redirecting_type.py

import abc
import typing

import pydantic


class File(pydantic.BaseModel, abc.ABC):
    @classmethod
    def __get_validators__(cls):
        # one or more validators may be yielded which will be called in the
        # order to validate the input, each validator will receive as an input
        # the value returned from the previous validator
        yield cls.validate

    @classmethod
    def validate(cls, v):
        subclass_dict: typing.Dict[str, pydantic.BaseModel] = {
            sbc.__name__: sbc for sbc in cls.__subclasses__()
        }

        match = list(set(subclass_dict.keys()).intersection(v.keys()))

        if not match:
            raise ValueError("Couldn't find a File type matching input: {}".format(v))

        classname = match[0]
        return subclass_dict[classname].parse_obj(v[classname])

    @abc.abstractmethod
    def open(self, *args, **kwargs) -> typing.IO:
        raise NotImplementedError


class S3File(File):
    bucket: str
    key: str

    def open(self, *args, **kwargs) -> typing.IO:
        raise NotImplementedError


class LocalFile(File):
    path: str

    def open(self, mode="r", *args, **kwargs) -> typing.IO:
        return open(self.path, mode, *args, **kwargs)


class Configuration(pydantic.BaseModel):
    """
    This model will be created from the
    data above using the BaseModel.parse_obj()
    classmethod.
    """

    source: File


data = {"source": {"LocalFile": {"path": "/tmp/test.txt"}}}

config: Configuration = Configuration.parse_obj(data)
with config.source.open() as f:
    print(f.read())