pydantic-super-model 2.0.0

Lightweight mixin for generic introspection and Annotated field lookup

Pydantic Super Model

A lightweight mixin for generic type introspection and Annotated field lookup. Works with any Python class, with optional Pydantic integration.

Two classes:

Class	Base	Key extras
SuperModelMixin	Any class	Framework-agnostic annotation introspection
SuperModelPydanticMixin	Pydantic BaseModel	Auto FieldNotImplemented validation, omits unset default None values

from pydantic_super_model import AnnotatedFieldInfo, FieldNotImplemented, SuperModelMixin, SuperModelPydanticMixin

Installation

pip install pydantic-super-model

Quick Start

With any Python class

from typing import Annotated

from pydantic_super_model import SuperModelMixin


class PrimaryKeyAnnotation:
    pass


PrimaryKey = Annotated[int, PrimaryKeyAnnotation]


class User(SuperModelMixin):
    id: PrimaryKey
    name: str

    def __init__(self, id: PrimaryKey, name: str) -> None:
        self.id = id
        self.name = name


user = User(id=1, name="John Doe")
field_info = user.get_annotated_fields(PrimaryKey)["id"]

assert field_info.value == 1
assert field_info.annotation == PrimaryKey
assert field_info.metadata == (PrimaryKeyAnnotation,)

With Pydantic

from typing import Annotated

from pydantic_super_model import SuperModelPydanticMixin


class PrimaryKeyAnnotation:
    pass


PrimaryKey = Annotated[int, PrimaryKeyAnnotation]


class User(SuperModelPydanticMixin):
    id: PrimaryKey
    name: str


user = User(id=1, name="John Doe")
field_info = user.get_annotated_fields(PrimaryKey)["id"]

assert field_info.value == 1
assert field_info.annotation == PrimaryKey
assert field_info.metadata == (PrimaryKeyAnnotation,)

API

get_annotated_fields(*annotations)

Return a dictionary of field names to AnnotatedFieldInfo for fields whose type hints carry any requested annotation.

• Match by the full Annotated[...] alias or by metadata type
• Include falsy values such as 0

SuperModelPydanticMixin only: unset default None values are omitted. Explicitly provided None is included.

class UserOptional(SuperModelPydanticMixin):
    id: PrimaryKey | None = None
    name: str


# Unset default None is omitted
assert not UserOptional(name="A").get_annotated_fields(PrimaryKey)

# Explicitly provided None is included
field_info = UserOptional(id=None, name="B").get_annotated_fields(PrimaryKey)["id"]
assert field_info.value is None

SuperModelMixin: all None values are included regardless of whether they were explicitly set.

get_annotated_field_value(annotation, allow_none=False, allow_undefined=False)

Return the first matching AnnotatedFieldInfo.

• Raises ValueError if no matching field exists (unless allow_undefined=True)
• Raises ValueError if the matched value is None (unless allow_none=True)

field_info = user.get_annotated_field_value(PrimaryKey)

assert field_info.value == 1

get_type()

Return the concrete generic type parameter supplied to the instance, or None.

from typing import Generic, TypeVar

from pydantic_super_model import SuperModelMixin

GenericType = TypeVar("GenericType")


class UserWithType(SuperModelMixin, Generic[GenericType]):
    id: GenericType
    name: str

    def __init__(self, id: GenericType, name: str) -> None:
        self.id = id
        self.name = name


assert UserWithType[int](id=1, name="Charlie").get_type() is int

validate_not_implemented_fields()

Reject fields annotated with FieldNotImplemented. Raises NotImplementedError if any such fields have values.

SuperModelPydanticMixin: called automatically on construction.

from typing import Annotated

from pydantic_super_model import FieldNotImplemented, SuperModelPydanticMixin


class Experimental(SuperModelPydanticMixin):
    test_field: Annotated[int, FieldNotImplemented]
    name: str


Experimental(test_field=1, name="x")  # raises NotImplementedError

SuperModelMixin: call manually in __init__ or __post_init__.

from typing import Annotated

from pydantic_super_model import FieldNotImplemented, SuperModelMixin


class Experimental(SuperModelMixin):
    test_field: Annotated[int, FieldNotImplemented]
    name: str

    def __init__(self, test_field: int, name: str) -> None:
        self.test_field = test_field
        self.name = name
        self.validate_not_implemented_fields()


Experimental(test_field=1, name="x")  # raises NotImplementedError

AnnotatedFieldInfo

A NamedTuple returned by get_annotated_fields and get_annotated_field_value:

Field	Type	Description
value	Any	The field's current value
annotation	object	The full type annotation
metadata	tuple[object, ...]	All metadata from Annotated
matched_metadata	tuple[object, ...]	Only the metadata that matched the query

Metadata Instance Matching

When you pass a class (not an instance) to get_annotated_fields, it matches metadata by isinstance:

from typing import Annotated

from pydantic_super_model import SuperModelPydanticMixin


class ThemeColorOptions:
    def __init__(self, *, palette: str, allow_gradients: bool) -> None:
        self.palette = palette
        self.allow_gradients = allow_gradients


ThemeColorField = Annotated[
    str,
    "theme_color",
    ThemeColorOptions(palette="northern-lights", allow_gradients=True),
]


class ThemeConfig(SuperModelPydanticMixin):
    accent_color: ThemeColorField


theme = ThemeConfig(accent_color="#7dd3fc")
field_info = theme.get_annotated_fields(ThemeColorOptions)["accent_color"]

assert isinstance(field_info.matched_metadata[0], ThemeColorOptions)
assert field_info.matched_metadata[0].palette == "northern-lights"
assert field_info.matched_metadata[0].allow_gradients is True

Development

Install dev dependencies:

pip install "pydantic-super-model[dev]"

Run the test suite:

pytest