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models

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create_pydantic_model(model_cls: Type[BaseModel], _use_pydantic_construct: bool = PYDANTIC_USE_CONSTRUCT, **field_values: Any)

Source code in kiara/utils/models.py 
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def create_pydantic_model(
    model_cls: Type[BaseModel],
    _use_pydantic_construct: bool = PYDANTIC_USE_CONSTRUCT,
    **field_values: Any,
):

    if _use_pydantic_construct:
        raise NotImplementedError()
        return model_cls.construct(**field_values)
    else:
        return model_cls(**field_values)

retrieve_data_subcomponent_keys(data: Any) -> Iterable[str]

Source code in kiara/utils/models.py 
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def retrieve_data_subcomponent_keys(data: Any) -> Iterable[str]:

    if hasattr(data, "__custom_root_type__") and data.__custom_root_type__:
        if isinstance(data.__root__, Mapping):  # type: ignore
            result = set()
            for k, v in data.__root__.items():  # type: ignore
                if isinstance(v, BaseModel):
                    result.add(k.split(".")[0])
            return result
        else:
            return []
    elif isinstance(data, BaseModel):
        matches = sorted(data.__fields__.keys())
        return matches
    else:
        log_message(
            f"No subcomponents retrieval supported for data of type: {type(data)}"
        )
        return []

get_subcomponent_from_model(data: KiaraModel, path: str) -> KiaraModel

Return subcomponents of a model under a specified path.

Source code in kiara/utils/models.py 
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def get_subcomponent_from_model(data: "KiaraModel", path: str) -> "KiaraModel":
    """Return subcomponents of a model under a specified path."""

    if "." in path:
        first_token, rest = path.split(".", maxsplit=1)
        sc = data.get_subcomponent(first_token)
        return sc.get_subcomponent(rest)

    if hasattr(data, "__custom_root_type__") and data.__custom_root_type__:
        if isinstance(data.__root__, Mapping):  # type: ignore
            if path in data.__root__.keys():  # type: ignore
                return data.__root__[path]  # type: ignore
            else:
                matches = {}
                for k in data.__root__.keys():  # type: ignore
                    if k.startswith(f"{path}."):
                        rest = k[len(path) + 1 :]
                        matches[rest] = data.__root__[k]  # type: ignore

                if not matches:
                    raise KeyError(f"No child models under '{path}'.")
                else:
                    raise NotImplementedError()
                    # subcomponent_group = KiaraModelGroup.create_from_child_models(**matches)
                    # return subcomponent_group

        else:
            raise NotImplementedError()
    else:
        if path in data.__fields__.keys():
            return getattr(data, path)
        else:
            raise KeyError(
                f"No subcomponent for key '{path}' in model: {data.instance_id}."
            )

assemble_subcomponent_graph(data: KiaraModel) -> Union[nx.DiGraph, None]

Source code in kiara/utils/models.py 
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def assemble_subcomponent_graph(data: "KiaraModel") -> Union[nx.DiGraph, None]:

    from kiara.models import KiaraModel

    graph = nx.DiGraph()

    def assemble_graph(info_model: KiaraModel, current_node_id, level: int = 0):
        graph.add_node(current_node_id, obj=info_model, level=level)
        scn = info_model.subcomponent_keys
        if not scn:
            return
        for child_path in scn:
            child_obj = info_model.get_subcomponent(child_path)
            new_node_id = f"{current_node_id}.{child_path}"
            graph.add_edge(current_node_id, new_node_id)
            if isinstance(child_obj, KiaraModel):
                assemble_graph(child_obj, new_node_id, level + 1)

    assemble_graph(data, KIARA_DEFAULT_ROOT_NODE_ID)
    return graph

create_subcomponent_tree_renderable(data: KiaraModel, show_data: bool = False) -> Tree

Source code in kiara/utils/models.py 
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def create_subcomponent_tree_renderable(
    data: "KiaraModel", show_data: bool = False
) -> Tree:

    from kiara.models import KiaraModel
    from kiara.utils.output import extract_renderable

    def extract_type_string(obj: Any) -> str:

        if isinstance(obj, KiaraModel):
            return f"model: {obj.model_type_id}"
        elif isinstance(obj, Mapping):
            return "dict"
        else:
            return type(obj).__name__

    def assemble_tree(node: Tree, model: Any, level: int):

        if isinstance(model, Mapping) and model:
            for k, v in model.items():
                child_tree = node.add(f"[b i]{k}[/b i] ({extract_type_string(v)})")
                assemble_tree(node=child_tree, model=v, level=level + 1)
            return

        if not isinstance(model, KiaraModel):
            if show_data:
                renderable = extract_renderable(model)
                panel = Panel(
                    renderable, title="[i]data[/i]", title_align="left", expand=False
                )
                node.add(panel)
            return

        scn = model.subcomponent_keys
        if not scn:
            return
        for child_path in scn:
            child_obj = model.get_subcomponent(child_path)
            child_tree = node.add(
                f"[b i]{child_path}[/b i] ({extract_type_string(child_obj)})"
            )
            assemble_tree(node=child_tree, model=child_obj, level=level + 1)

    tree = Tree(f"[b]{data.model_type_id}[/b]: [b]{data.instance_id}[/b]")
    assemble_tree(node=tree, model=data, level=0)

    return tree