chore(pyproject.toml): remove unused python-box dependency

chore(pyproject.toml): add griffe dependency for documentation generation
refactor(base.py): remove BetterDumperMixin and related code to simplify model serialization

pyproject.toml

@@ -30,7 +30,6 @@ pendulum = "^3.0.0"
 pint = "0.24.*"
 pycognito = "2024.5.1"
 pydantic = "2.7.3"
-python-box = "^7.2.0"
 
 [tool.poetry.group.dev.dependencies]
 aioresponses = "0.7.6"
@@ -66,6 +65,7 @@ mkdocstrings-python = "1.10.3"
 pkginfo = "<1.11"
 setuptools = "^70.0.0"
 virtualenv = "^20.26.2"
+griffe = "^1.3.1"
 
 
 [build-system]

src/otf_api/models/base.py

@@ -1,136 +1,9 @@
-import inspect
-import typing
-from typing import ClassVar, TypeVar
+from typing import ClassVar
 
-from box import Box
 from pydantic import BaseModel, ConfigDict
 
-if typing.TYPE_CHECKING:
-    from pydantic.main import IncEx
 
-T = TypeVar("T", bound="OtfItemBase")
-
-
-class BetterDumperMixin:
-    """A better dumper for Pydantic models that includes properties in the dumped data. Must be mixed
-    into a Pydantic model, as it overrides the `model_dump` method.
-
-    Includes support for nested models, and has an option to not include properties when dumping.
-    """
-
-    def get_properties(self) -> list[str]:
-        """Get the properties of the model."""
-        cls = type(self)
-
-        properties: list[str] = []
-        methods = inspect.getmembers(self, lambda f: not (inspect.isroutine(f)))
-        for prop_name, _ in methods:
-            if hasattr(cls, prop_name) and isinstance(getattr(cls, prop_name), property):
-                properties.append(prop_name)
-
-        return properties
-
-    @typing.overload
-    def model_dump(
-        self,
-        *,
-        mode: typing.Literal["json", "python"] | str = "python",
-        include: "IncEx" = None,
-        exclude: "IncEx" = None,
-        by_alias: bool = False,
-        exclude_unset: bool = False,
-        exclude_defaults: bool = False,
-        exclude_none: bool = False,
-        round_trip: bool = False,
-        warnings: bool = True,
-        include_properties: bool = True,
-    ) -> Box[str, typing.Any]: ...
-
-    @typing.overload
-    def model_dump(
-        self,
-        *,
-        mode: typing.Literal["json", "python"] | str = "python",
-        include: "IncEx" = None,
-        exclude: "IncEx" = None,
-        by_alias: bool = False,
-        exclude_unset: bool = False,
-        exclude_defaults: bool = False,
-        exclude_none: bool = False,
-        round_trip: bool = False,
-        warnings: bool = True,
-        include_properties: bool = False,
-    ) -> dict[str, typing.Any]: ...
-
-    def model_dump(
-        self,
-        *,
-        mode: typing.Literal["json", "python"] | str = "python",
-        include: "IncEx" = None,
-        exclude: "IncEx" = None,
-        by_alias: bool = False,
-        exclude_unset: bool = False,
-        exclude_defaults: bool = False,
-        exclude_none: bool = False,
-        round_trip: bool = False,
-        warnings: bool = True,
-        include_properties: bool = True,
-    ) -> dict[str, typing.Any] | Box[str, typing.Any]:
-        """Usage docs: https://docs.pydantic.dev/2.4/concepts/serialization/#modelmodel_dump
-
-        Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
-
-        Args:
-            mode: The mode in which `to_python` should run.
-                If mode is 'json', the dictionary will only contain JSON serializable types.
-                If mode is 'python', the dictionary may contain any Python objects.
-            include: A list of fields to include in the output.
-            exclude: A list of fields to exclude from the output.
-            by_alias: Whether to use the field's alias in the dictionary key if defined.
-            exclude_unset: Whether to exclude fields that are unset or None from the output.
-            exclude_defaults: Whether to exclude fields that are set to their default value from the output.
-            exclude_none: Whether to exclude fields that have a value of `None` from the output.
-            round_trip: Whether to enable serialization and deserialization round-trip support.
-            warnings: Whether to log warnings when invalid fields are encountered.
-            include_properties: Whether to include properties in the dumped data.
-
-        Returns:
-            A dictionary representation of the model. Will be a `Box` if `include_properties` is `True`, otherwise a
-            regular dictionary.
-
-        """
-        dumped_data = typing.cast(BaseModel, super()).model_dump(
-            mode=mode,
-            include=include,
-            exclude=exclude,
-            by_alias=by_alias,
-            exclude_unset=exclude_unset,
-            exclude_defaults=exclude_defaults,
-            exclude_none=exclude_none,
-            round_trip=round_trip,
-            warnings=warnings,
-        )
-
-        if not include_properties:
-            return dumped_data
-
-        properties = self.get_properties()
-
-        # set properties to their values
-        for prop_name in properties:
-            dumped_data[prop_name] = getattr(self, prop_name)
-
-        # if the property is a Pydantic model, dump it as well
-        for k, v in dumped_data.items():
-            if issubclass(type(getattr(self, k)), BaseModel):
-                dumped_data[k] = getattr(self, k).model_dump()
-            elif hasattr(v, "model_dump"):
-                dumped_data[k] = v.model_dump()
-
-        return Box(dumped_data)
-
-
-class OtfItemBase(BetterDumperMixin, BaseModel):
+class OtfItemBase(BaseModel):
     model_config: ClassVar[ConfigDict] = ConfigDict(arbitrary_types_allowed=True, extra="allow")