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functions

openml.extensions.functions #

get_extension_by_flow #

get_extension_by_flow(flow: OpenMLFlow, raise_if_no_extension: bool = False) -> Extension | None

Get an extension which can handle the given flow.

Iterates all registered extensions and checks whether they can handle the presented flow. Raises an exception if two extensions can handle a flow.

PARAMETER DESCRIPTION
flow

TYPE: OpenMLFlow

raise_if_no_extension

Raise an exception if no registered extension can handle the presented flow.

TYPE: bool (optional DEFAULT: False)

RETURNS DESCRIPTION
Extension or None
Source code in openml/extensions/functions.py 
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def get_extension_by_flow(
    flow: OpenMLFlow,
    raise_if_no_extension: bool = False,  # noqa: FBT002
) -> Extension | None:
    """Get an extension which can handle the given flow.

    Iterates all registered extensions and checks whether they can handle the presented flow.
    Raises an exception if two extensions can handle a flow.

    Parameters
    ----------
    flow : OpenMLFlow

    raise_if_no_extension : bool (optional, default=False)
        Raise an exception if no registered extension can handle the presented flow.

    Returns
    -------
    Extension or None
    """
    # import openml_sklearn to register SklearnExtension
    if importlib.util.find_spec("openml_sklearn"):
        import openml_sklearn  # noqa: F401

    candidates = []
    for extension_class in openml.extensions.extensions:
        if extension_class.can_handle_flow(flow):
            candidates.append(extension_class())
    if len(candidates) == 0:
        if raise_if_no_extension:
            install_instruction = ""
            if flow.name.startswith("sklearn"):
                install_instruction = SKLEARN_HINT
            raise ValueError(
                f"No extension registered which can handle flow: {flow.flow_id} ({flow.name}). "
                f"{install_instruction}"
            )

        return None

    if len(candidates) == 1:
        return candidates[0]

    raise ValueError(
        f"Multiple extensions registered which can handle flow: {flow}, but only one "
        f"is allowed ({candidates}).",
    )

get_extension_by_model #

get_extension_by_model(model: Any, raise_if_no_extension: bool = False) -> Extension | None

Get an extension which can handle the given flow.

Iterates all registered extensions and checks whether they can handle the presented model. Raises an exception if two extensions can handle a model.

PARAMETER DESCRIPTION
model

TYPE: Any

raise_if_no_extension

Raise an exception if no registered extension can handle the presented model.

TYPE: bool (optional DEFAULT: False)

RETURNS DESCRIPTION
Extension or None
Source code in openml/extensions/functions.py 
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def get_extension_by_model(
    model: Any,
    raise_if_no_extension: bool = False,  # noqa: FBT002
) -> Extension | None:
    """Get an extension which can handle the given flow.

    Iterates all registered extensions and checks whether they can handle the presented model.
    Raises an exception if two extensions can handle a model.

    Parameters
    ----------
    model : Any

    raise_if_no_extension : bool (optional, default=False)
        Raise an exception if no registered extension can handle the presented model.

    Returns
    -------
    Extension or None
    """
    # import openml_sklearn to register SklearnExtension
    if importlib.util.find_spec("openml_sklearn"):
        import openml_sklearn  # noqa: F401

    candidates = []
    for extension_class in openml.extensions.extensions:
        if extension_class.can_handle_model(model):
            candidates.append(extension_class())
    if len(candidates) == 0:
        if raise_if_no_extension:
            install_instruction = ""
            if type(model).__module__.startswith("sklearn"):
                install_instruction = SKLEARN_HINT
            raise ValueError(
                f"No extension registered which can handle model: {model}. {install_instruction}"
            )

        return None

    if len(candidates) == 1:
        return candidates[0]

    raise ValueError(
        f"Multiple extensions registered which can handle model: {model}, but only one "
        f"is allowed ({candidates}).",
    )

register_extension #

register_extension(extension: type[Extension]) -> None

Register an extension.

Registered extensions are considered by get_extension_by_flow and get_extension_by_model, which are used by openml.flow and openml.runs.

PARAMETER DESCRIPTION
extension

TYPE: Type[Extension]

RETURNS DESCRIPTION
None
Source code in openml/extensions/functions.py 
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def register_extension(extension: type[Extension]) -> None:
    """Register an extension.

    Registered extensions are considered by ``get_extension_by_flow`` and
    ``get_extension_by_model``, which are used by ``openml.flow`` and ``openml.runs``.

    Parameters
    ----------
    extension : Type[Extension]

    Returns
    -------
    None
    """
    openml.extensions.extensions.append(extension)