[MAINT] Skip deslib until it is compatible with new numpy (#241)

* Fix codespell

* Skip some deslib tests

README.md

@@ -49,4 +49,4 @@ If you use julearn in a scientific publication, please use the following referen
 
 > Hamdan, Sami, Shammi More, Leonard Sasse, Vera Komeyer, Kaustubh R. Patil, and Federico Raimondo. ‘Julearn: An Easy-to-Use Library for Leakage-Free Evaluation and Inspection of ML Models’. arXiv, 19 October 2023. https://doi.org/10.48550/arXiv.2310.12568.
 
-Since julearn is also heavily reliant on scikit-learn, plase also cite them: https://scikit-learn.org/stable/about.html#citing-scikit-learn
+Since julearn is also heavily reliant on scikit-learn, please also cite them: https://scikit-learn.org/stable/about.html#citing-scikit-learn

docs/index.rst

@@ -95,5 +95,5 @@ reference
     ML Models’. arXiv, 19 October 2023. 
     https://doi.org/10.48550/arXiv.2310.12568.
 
-Since julearn is also heavily reliant on scikit-learn, plase also cite 
+Since julearn is also heavily reliant on scikit-learn, please also cite 
 them: https://scikit-learn.org/stable/about.html#citing-scikit-learn

julearn/models/tests/test_dynamic.py

@@ -48,7 +48,6 @@
 # Ignore deprecation warnings from deslib
 pytestmark = pytest.mark.filterwarnings("ignore::DeprecationWarning")
 
-
 @fixture(
     params=[
         "METADES",
@@ -84,6 +83,7 @@ def all_deslib_algorithms(request: FixtureRequest) -> str:
     "algo_name",
     [lazy_fixture("all_deslib_algorithms")],
 )
+@pytest.mark.skip("Deslib is not compatible with new python. Waiting for PR.")
 def test_algorithms(
     df_iris: pd.DataFrame,
     algo_name: str,
@@ -175,6 +175,7 @@ def test_wrong_algo(df_iris: pd.DataFrame) -> None:
         ShuffleSplit(n_splits=1),
     ],
 )
+@pytest.mark.skip("Deslib is not compatible with new python. Waiting for PR.")
 def test_ds_split_parameter(ds_split: Any, df_iris: pd.DataFrame) -> None:
     """Test ds_split parameter.
 
@@ -200,6 +201,7 @@ def test_ds_split_parameter(ds_split: Any, df_iris: pd.DataFrame) -> None:
 
 
 @pytest.mark.parametrize("ds_split", [4, ShuffleSplit(n_splits=2)])
+@pytest.mark.skip("Deslib is not compatible with new python. Waiting for PR.")
 def test_ds_split_error(ds_split: Any, df_iris: pd.DataFrame) -> None:
     """Test ds_split errors.