[FEATURE] - Create ImmutableDict class for .keywords.

[coltonbh]

Further protection from modification of key structures. Something like this though this doesn't quite work yet:

from collections.abc import Mapping

from pydantic import BaseModel
from typing import Any, Dict, Iterator, Tuple


class ImmutableDict(Mapping):
    def __init__(self, data: Dict[str, Any]):
        self._data = dict(data)

    def __getitem__(self, key: str) -> Any:
        return self._data[key]

    def __iter__(self) -> Iterator[str]:
        return iter(self._data)

    def __len__(self) -> int:
        return len(self._data)

    def __repr__(self) -> str:
        return f"{self.__class__.__name__}({self._data})"

    def __setitem__(self, key: str, value: Any) -> None:
        raise TypeError(f"{self.__class__.__name__} is immutable")

    def __delitem__(self, key: str) -> None:
        raise TypeError(f"{self.__class__.__name__} is immutable")

    def clear(self) -> None:
        raise TypeError(f"{self.__class__.__name__} is immutable")

    def update(self, *args, **kwargs) -> None:
        raise TypeError(f"{self.__class__.__name__} is immutable")

    def pop(self, key: str, default: Any = None) -> Any:
        raise TypeError(f"{self.__class__.__name__} is immutable")

    def popitem(self) -> Tuple[str, Any]:
        raise TypeError(f"{self.__class__.__name__} is immutable")

    def setdefault(self, key: str, default: Any = None) -> Any:
        raise TypeError(f"{self.__class__.__name__} is immutable")

    @classmethod
    def __get_pydantic_core_schema__(cls, source: type, handler: Any) -> Any:
        return handler.generate_schema(Dict[str, Any])


class _KeywordsMixin(BaseModel):
    keywords: Dict[str, Any] = {}


class _KeywordsMixinIm(BaseModel):
    keywords: ImmutableDict = {}


kw = {"a": 1, "b": 2}
mkw = _KeywordsMixin(keywords=kw)
mkw.model_dump()
print(mkw.keywords == kw)
print(mkw.keywords is kw)
mkwi = _KeywordsMixinIm(keywords=kw)
mkwi.model_dump()
print(mkwi.keywords == kw)
print(mkwi.keywords is kw)