"""Transformers for missing value imputation."""

# Authors: The scikit-learn developers
# SPDX-License-Identifier: BSD-3-Clause

import typing

from ._base import MissingIndicator, SimpleImputer
from ._knn import KNNImputer

if typing.TYPE_CHECKING:
    # Avoid errors in type checkers (e.g. mypy) for experimental estimators.
    # TODO: remove this check once the estimator is no longer experimental.
    from ._iterative import IterativeImputer  # noqa: F401

__all__ = ["KNNImputer", "MissingIndicator", "SimpleImputer"]


# TODO: remove this check once the estimator is no longer experimental.
def __getattr__(name):
    if name == "IterativeImputer":
        raise ImportError(
            f"{name} is experimental and the API might change without any "
            "deprecation cycle. To use it, you need to explicitly import "
            "enable_iterative_imputer:\n"
            "from sklearn.experimental import enable_iterative_imputer"
        )
    raise AttributeError(f"module {__name__} has no attribute {name}")
