Fix linting

julearn/api.py

@@ -26,7 +26,7 @@
 from .utils.typing import CVLike
 
 
-def _validata_api_params(
+def _validata_api_params(  # noqa: C901
     X: List[str],  # noqa: N803
     y: str,
     model: Union[str, PipelineCreator, BaseEstimator, List[PipelineCreator]],
@@ -116,6 +116,29 @@ def _validata_api_params(
           is provided for at least one hyperparameter, a search will be
           performed.
 
+    search_params : dict | None
+        Additional parameters in case Hyperparameter Tuning is performed, with
+        the following keys:
+
+        * 'kind': The kind of search algorithm to use, Valid options are:
+
+          * ``"grid"`` : :class:`~sklearn.model_selection.GridSearchCV`
+          * ``"random"`` :
+            :class:`~sklearn.model_selection.RandomizedSearchCV`
+          * ``"bayes"`` : :class:`~skopt.BayesSearchCV`
+          * ``"optuna"`` :
+            :class:`~optuna_integration.OptunaSearchCV`
+          * user-registered searcher name : see
+            :func:`~julearn.model_selection.register_searcher`
+          * ``scikit-learn``-compatible searcher
+
+        * 'cv': If a searcher is going to be used, the cross-validation
+            splitting strategy to use. Defaults to same CV as for the model
+            evaluation.
+        * 'scoring': If a searcher is going to be used, the scoring metric to
+            evaluate the performance.
+
+        See :ref:`hp_tuning` for details.
     seed : int | None
         If not None, set the random seed before any operation. Useful for
         reproducibility.
@@ -138,6 +161,7 @@ def _validata_api_params(
         Whether to wrap the score or not.
     problem_type : str
         The problem type.
+
     """
     if return_estimator not in [None, "final", "cv", "all"]:
         raise_error(