Create function to test if the polars module is available. Use it to …

…xfail specific tests

skrub/_dataframe/_namespace.py

@@ -43,6 +43,19 @@ def is_polars(dataframe):
     return isinstance(dataframe, (pl.DataFrame, pl.LazyFrame))
 
 
+def is_namespace_pandas(px):
+    return px is pd
+
+
+def is_namespace_polars(px):
+    if "polars" not in sys.modules:
+        return False
+
+    import polars as pl
+
+    return px is pl
+
+
 def get_df_namespace(*dfs):
     """Get the namespaces of dataframes.
 

skrub/tests/test_datetime_encoder.py

@@ -7,6 +7,7 @@
 from numpy.testing import assert_allclose, assert_array_equal
 from pandas.testing import assert_frame_equal
 
+from skrub._dataframe._namespace import is_namespace_polars
 from skrub._dataframe._polars import POLARS_SETUP
 from skrub._datetime_encoder import (
     TIME_LEVELS,
@@ -352,7 +353,7 @@ def test_transform_nan(px):
 
 @pytest.mark.parametrize("px", MODULES)
 def test_mixed_type_dataframe(px):
-    if px.__name__ == "polars":
+    if is_namespace_polars(px):
         pytest.xfail(
             reason=(
                 "to_datetime(X) raises polars.exceptions.ComputeError: cannot cast"

skrub/tests/test_fuzzy_join.py

@@ -9,6 +9,7 @@
 from sklearn.feature_extraction.text import HashingVectorizer
 
 from skrub import fuzzy_join
+from skrub._dataframe._namespace import is_namespace_polars
 from skrub._dataframe._polars import POLARS_SETUP
 
 MODULES = [pd]
@@ -31,7 +32,7 @@ def test_fuzzy_join(px, analyzer: Literal["char", "char_wb", "word"]):
     """
     Testing if fuzzy_join results are as expected.
     """
-    if px.__name__ == "polars":
+    if is_namespace_polars(px):
         pytest.xfail(reason="Polars DataFrame object has no attribute 'reset_index'")
     df1 = px.DataFrame({"a1": ["ana", "lala", "nana et sana", np.NaN]})
     df2 = px.DataFrame({"a2": ["anna", "lala et nana", "lana", "sana", np.NaN]})
@@ -97,7 +98,7 @@ def test_fuzzy_join(px, analyzer: Literal["char", "char_wb", "word"]):
 
 @pytest.mark.parametrize("px", MODULES)
 def test_match_score(px):
-    if px.__name__ == "polars":
+    if is_namespace_polars(px):
         pytest.xfail(reason="Polars DataFrame object has no attribute 'reset_index'")
     left = px.DataFrame({"A": ["aa", "bb"]})
     right = px.DataFrame({"A": ["aa", "ba"], "B": [1, 2]})
@@ -109,7 +110,7 @@ def test_match_score(px):
 
 @pytest.mark.parametrize("px", MODULES)
 def test_perfect_matches(px):
-    if px.__name__ == "polars":
+    if is_namespace_polars(px):
         pytest.xfail(reason="Polars DataFrame object has no attribute 'reset_index'")
     # non-regression test for https://github.com/skrub-data/skrub/issues/764
     # fuzzy_join when all rows had a perfect match used to trigger a division by 0
@@ -126,7 +127,7 @@ def test_fuzzy_join_dtypes(px):
     """
     Test that the dtypes of dataframes are maintained after join
     """
-    if px.__name__ == "polars":
+    if is_namespace_polars(px):
         pytest.xfail(reason="Polars DataFrame object has no attribute 'reset_index'")
     a = px.DataFrame({"col1": ["aaa", "bbb"], "col2": [1, 2]})
     b = px.DataFrame({"col1": ["aaa_", "bbb_"], "col3": [1, 2]})
@@ -171,7 +172,7 @@ def test_parameters_error(px, analyzer, on, how) -> None:
 
 @pytest.mark.parametrize("px", MODULES)
 def test_missing_keys(px):
-    if px.__name__ == "polars":
+    if is_namespace_polars(px):
         pytest.xfail(reason="Polars DataFrame object has no attribute 'reset_index'")
     a = px.DataFrame({"col1": ["aaa", "bbb"], "col2": [1, 2]})
     b = px.DataFrame({"col1": ["aaa_", "bbb_"], "col3": [1, 2]})
@@ -190,7 +191,7 @@ def test_missing_keys(px):
 
 @pytest.mark.parametrize("px", MODULES)
 def test_drop_unmatched(px):
-    if px.__name__ == "polars":
+    if is_namespace_polars(px):
         pytest.xfail(reason="Polars DataFrame object has no attribute 'reset_index'")
     a = px.DataFrame({"col1": ["aaaa", "bbb", "ddd dd"], "col2": [1, 2, 3]})
     b = px.DataFrame({"col1": ["aaa_", "bbb_", "cc ccc"], "col3": [1, 2, 3]})
@@ -214,7 +215,7 @@ def test_how_param(px):
     Test correct shape of left and right joins.
     Also test if an error is raised when an incorrect parameter value is passed.
     """
-    if px.__name__ == "polars":
+    if is_namespace_polars(px):
         pytest.xfail(reason="Polars DataFrame object has no attribute 'reset_index'")
     a = px.DataFrame({"col1": ["aaaa", "bbb", "ddd dd"], "col2": [1, 2, 3]})
     b = px.DataFrame(
@@ -290,7 +291,7 @@ def test_correct_encoder(px):
     """
     Test that the encoder error checking is working as intended.
     """
-    if px.__name__ == "polars":
+    if is_namespace_polars(px):
         pytest.xfail(reason="Polars DataFrame object has no attribute 'reset_index'")
 
     class TestVectorizer(HashingVectorizer):
@@ -337,7 +338,7 @@ def test_numerical_column(px):
     """
     Testing that fuzzy_join works with numerical columns.
     """
-    if px.__name__ == "polars":
+    if is_namespace_polars(px):
         pytest.xfail(reason="Polars DataFrame object has no attribute 'reset_index'")
     left = px.DataFrame({"str1": ["aa", "a", "bb"], "int": [10, 2, 5]})
     right = px.DataFrame(
@@ -371,7 +372,7 @@ def test_datetime_column(px, assert_frame_equal_):
     """
     Testing that fuzzy_join works with datetime columns.
     """
-    if px.__name__ == "polars":
+    if is_namespace_polars(px):
         pytest.xfail(reason="Module 'polars' has no attribute 'to_datetime'")
     left = px.DataFrame(
         {
@@ -423,7 +424,7 @@ def test_mixed_joins(px, assert_frame_equal_):
     """
     Test fuzzy joining on mixed and multiple column types.
     """
-    if px.__name__ == "polars":
+    if is_namespace_polars(px):
         pytest.xfail(reason="Module 'polars' has no attribute 'to_datetime'")
     left = px.DataFrame(
         {
@@ -569,7 +570,7 @@ def test_iterable_input(px):
     """
     Test if iterable input: list, set, dictionary or tuple works.
     """
-    if px.__name__ == "polars":
+    if is_namespace_polars(px):
         pytest.xfail(reason="Polars DataFrame object has no attribute 'reset_index'")
     df1 = px.DataFrame(
         {"a": ["ana", "lala", "nana"], "str2": ["Texas", "France", "Greek God"]}
@@ -594,7 +595,7 @@ def test_missing_values(px):
     """
     Test fuzzy joining on missing values.
     """
-    if px.__name__ == "polars":
+    if is_namespace_polars(px):
         pytest.xfail(reason="Polars DataFrame object has no attribute 'reset_index'")
     a = px.DataFrame({"col1": ["aaaa", "bbb", "ddd dd"], "col2": [1, 2, 3]})
     b = px.DataFrame({"col3": [np.NaN, "bbb", "ddd dd"], "col4": [1, 2, 3]})

skrub/tests/test_gap_encoder.py

@@ -5,6 +5,7 @@
 from sklearn.model_selection import train_test_split
 
 from skrub import GapEncoder
+from skrub._dataframe._namespace import is_namespace_polars
 from skrub._dataframe._polars import POLARS_SETUP
 from skrub.datasets import fetch_midwest_survey
 from skrub.tests.utils import generate_data
@@ -222,7 +223,7 @@ def test_score(n_samples: int = 70):
 )
 def test_missing_values(px, missing: str):
     """Test what happens when missing values are in the data"""
-    if px.__name__ == "polars":
+    if is_namespace_polars(px):
         pytest.xfail(
             reason=(
                 "'TypeError: '<' not supported between instances of 'DataTypeClass' and"

skrub/tests/test_interpolation_join.py

@@ -6,6 +6,7 @@
 from sklearn.neighbors import KNeighborsClassifier, KNeighborsRegressor
 
 from skrub import InterpolationJoiner
+from skrub._dataframe._namespace import is_namespace_polars
 from skrub._dataframe._polars import POLARS_SETUP
 
 MODULES = [pd]
@@ -39,7 +40,7 @@ def weather():
 @pytest.mark.parametrize("key", [["latitude", "longitude"], "latitude"])
 @pytest.mark.parametrize("with_nulls", [False, True])
 def test_interpolation_join(px, buildings, weather, key, with_nulls):
-    if px.__name__ == "polars":
+    if is_namespace_polars(px):
         pytest.xfail(
             reason=(
                 "In polars, DataFrame.drop() got an unexpected keyword argument 'axis'"
@@ -60,7 +61,7 @@ def test_interpolation_join(px, buildings, weather, key, with_nulls):
 
 @pytest.mark.parametrize("px", MODULES)
 def test_vectorizer(px):
-    if px.__name__ == "polars":
+    if is_namespace_polars(px):
         pytest.xfail(
             reason=(
                 "In polars, DataFrame.drop() got an unexpected keyword argument 'axis'"
@@ -87,7 +88,7 @@ def transform(self, X):
 
 @pytest.mark.parametrize("px", MODULES)
 def test_no_multioutput(px, buildings, weather):
-    if px.__name__ == "polars":
+    if is_namespace_polars(px):
         pytest.xfail(
             reason=(
                 "In polars, DataFrame.drop() got an unexpected keyword argument 'axis'"
@@ -105,7 +106,7 @@ def test_no_multioutput(px, buildings, weather):
 
 @pytest.mark.parametrize("px", MODULES)
 def test_condition_choice(px):
-    if px.__name__ == "polars":
+    if is_namespace_polars(px):
         pytest.xfail(
             reason=(
                 "In polars, DataFrame.drop() got an unexpected keyword argument 'axis'"
@@ -143,7 +144,7 @@ def test_condition_choice(px):
 
 @pytest.mark.parametrize("px", MODULES)
 def test_suffix(px):
-    if px.__name__ == "polars":
+    if is_namespace_polars(px):
         pytest.xfail(
             reason=(
                 "In polars, DataFrame.drop() got an unexpected keyword argument 'axis'"
@@ -159,7 +160,7 @@ def test_suffix(px):
 
 @pytest.mark.parametrize("px", MODULES)
 def test_mismatched_indexes(px):
-    if px.__name__ == "polars":
+    if is_namespace_polars(px):
         pytest.xfail(
             reason=(
                 "In polars, DataFrame.drop() got an unexpected keyword argument 'axis'"
@@ -179,7 +180,7 @@ def test_mismatched_indexes(px):
 @pytest.mark.parametrize("px", MODULES)
 def test_fit_on_none(px):
     # X is hardly used in fit so it should be ok to fit without a main table
-    if px.__name__ == "polars":
+    if is_namespace_polars(px):
         pytest.xfail(
             reason=(
                 "In polars, DataFrame.drop() got an unexpected keyword argument 'axis'"
@@ -199,7 +200,7 @@ def test_fit_on_none(px):
 
 @pytest.mark.parametrize("px", MODULES)
 def test_join_on_date(px):
-    if px.__name__ == "polars":
+    if is_namespace_polars(px):
         pytest.xfail(
             reason=(
                 "In polars, DataFrame.drop() got an unexpected keyword argument 'axis'"
@@ -231,7 +232,7 @@ def fit(self, X, y):
 
 @pytest.mark.parametrize("px", MODULES)
 def test_fit_failures(px, buildings, weather):
-    if px.__name__ == "polars":
+    if is_namespace_polars(px):
         pytest.xfail(
             reason=(
                 "In polars, DataFrame.drop() got an unexpected keyword argument 'axis'"
@@ -281,7 +282,7 @@ def predict(self, X):
 
 @pytest.mark.parametrize("px", MODULES)
 def test_transform_failures(px, buildings, weather):
-    if px.__name__ == "polars":
+    if is_namespace_polars(px):
         pytest.xfail(
             reason=(
                 "In polars, DataFrame.drop() got an unexpected keyword argument 'axis'"
@@ -329,7 +330,7 @@ def test_transform_failures(px, buildings, weather):
 
 @pytest.mark.parametrize("px", MODULES)
 def test_transform_failures_dtype(px, buildings, weather):
-    if px.__name__ == "polars":
+    if is_namespace_polars(px):
         pytest.xfail(
             reason=(
                 "In polars, DataFrame.drop() got an unexpected keyword argument 'axis'"

skrub/tests/test_joiner.py

@@ -4,6 +4,7 @@
 from pandas.testing import assert_frame_equal
 
 from skrub import Joiner
+from skrub._dataframe._namespace import is_namespace_polars
 from skrub._dataframe._polars import POLARS_SETUP
 
 MODULES = [pd]
@@ -19,7 +20,7 @@
 
 @pytest.mark.parametrize("px", MODULES)
 def test_joiner(px):
-    if px.__name__ == "polars":
+    if is_namespace_polars(px):
         pytest.xfail(reason="Polars DataFrame object has no attribute 'reset_index'")
     main_table = px.DataFrame(
         {
@@ -65,7 +66,7 @@ def test_joiner(px):
 
 @pytest.mark.parametrize("px, assert_frame_equal_", ASSERT_TUPLES)
 def test_multiple_keys(px, assert_frame_equal_):
-    if px.__name__ == "polars":
+    if is_namespace_polars(px):
         pytest.xfail(reason="Polars DataFrame object has no attribute 'reset_index'")
     df = px.DataFrame(
         {"Co": ["France", "Italia", "Deutchland"], "Ca": ["Paris", "Roma", "Berlin"]}

skrub/tests/test_similarity_encoder.py

@@ -7,6 +7,7 @@
 from sklearn.exceptions import NotFittedError
 
 from skrub import SimilarityEncoder
+from skrub._dataframe._namespace import is_namespace_polars
 from skrub._dataframe._polars import POLARS_SETUP
 from skrub._similarity_encoder import ngram_similarity_matrix
 from skrub._string_distances import ngram_similarity
@@ -341,7 +342,7 @@ def test_check_fitted_super_vectorizer():
 
 @pytest.mark.parametrize("px", MODULES)
 def test_inverse_transform(px):
-    if px.__name__ == "polars":
+    if is_namespace_polars(px):
         pytest.xfail(reason="Setting output to polars is not possible yet.")
     encoder = SimilarityEncoder()
     encoder.set_output(transform="pandas")