chore: use Narwhals stable api

pyproject.toml

@@ -20,7 +20,7 @@ maintainers = [
 ]
 
 dependencies = [
-    "narwhals>=0.8.13",
+    "narwhals>=1.0.0",
     "pandas>=1.1.5",
     "scikit-learn>=1.0",
     "importlib-metadata >= 1.0; python_version < '3.8'",

sklego/linear_model.py

@@ -9,7 +9,7 @@
 from inspect import signature
 from warnings import warn
 
-import narwhals as nw
+import narwhals.stable.v1 as nw
 import numpy as np
 from scipy.optimize import minimize
 from scipy.special._ufuncs import expit

sklego/meta/_grouped_utils.py

@@ -2,7 +2,7 @@
 
 from typing import List
 
-import narwhals as nw
+import narwhals.stable.v1 as nw
 import pandas as pd
 from scipy.sparse import issparse
 from sklearn.utils import check_array

sklego/meta/_shrinkage_utils.py

@@ -1,6 +1,6 @@
 from functools import partial
 
-import narwhals as nw
+import narwhals.stable.v1 as nw
 import numpy as np
 from sklearn.utils.validation import check_is_fitted
 

sklego/meta/grouped_predictor.py

@@ -1,7 +1,7 @@
 from copy import deepcopy
 from typing import List, Union
 
-import narwhals as nw
+import narwhals.stable.v1 as nw
 import numpy as np
 import pandas as pd
 from sklearn import clone

sklego/meta/grouped_transformer.py

@@ -1,6 +1,6 @@
 from typing import Union
 
-import narwhals as nw
+import narwhals.stable.v1 as nw
 import numpy as np
 from sklearn.base import BaseEstimator, MetaEstimatorMixin, TransformerMixin, clone
 from sklearn.utils.validation import check_is_fitted

sklego/meta/hierarchical_predictor.py

@@ -1,6 +1,6 @@
 from warnings import warn
 
-import narwhals as nw
+import narwhals.stable.v1 as nw
 import numpy as np
 import pandas as pd
 from joblib import Parallel, delayed

sklego/meta/regression_outlier_detector.py

@@ -1,4 +1,4 @@
-import narwhals as nw
+import narwhals.stable.v1 as nw
 import numpy as np
 from sklearn import clone
 from sklearn.base import BaseEstimator, OutlierMixin

sklego/model_selection.py

@@ -3,7 +3,7 @@
 from itertools import combinations
 from warnings import warn
 
-import narwhals as nw
+import narwhals.stable.v1 as nw
 import numpy as np
 import pandas as pd
 from sklearn.exceptions import NotFittedError

sklego/pandas_utils.py

@@ -2,7 +2,7 @@
 import inspect
 from functools import partial, wraps
 
-import narwhals as nw
+import narwhals.stable.v1 as nw
 import numpy as np
 from scipy.ndimage import shift
 

sklego/preprocessing/pandastransformers.py

@@ -3,7 +3,7 @@
 import warnings
 from typing import Any
 
-import narwhals as nw
+import narwhals.stable.v1 as nw
 from narwhals.dependencies import get_pandas
 from sklearn.base import BaseEstimator, TransformerMixin
 from sklearn.utils.validation import check_is_fitted

sklego/preprocessing/projections.py

@@ -1,4 +1,4 @@
-import narwhals as nw
+import narwhals.stable.v1 as nw
 import numpy as np
 from sklearn.base import BaseEstimator, TransformerMixin
 from sklearn.utils import check_array

tests/test_meta/test_hierarchical_predictor.py

@@ -1,7 +1,7 @@
 from contextlib import nullcontext as does_not_raise
 from random import randint
 
-import narwhals as nw
+import narwhals.stable.v1 as nw
 import numpy as np
 import pandas as pd
 import polars as pl

tests/test_pandas_utils/test_pandas_utils.py

@@ -1,6 +1,6 @@
 import logging
 
-import narwhals as nw
+import narwhals.stable.v1 as nw
 import numpy as np
 import pandas as pd
 import polars as pl

tests/test_preprocessing/test_informationfilter.py

@@ -1,4 +1,4 @@
-import narwhals as nw
+import narwhals.stable.v1 as nw
 import numpy as np
 import pandas as pd
 import polars as pl