Update polars to 1.12.0 (#350)

* upgrade polars to 1.12.0

* upperpin

pyproject.toml

@@ -11,7 +11,7 @@ maintainers = [
   { name="Faisal Dosani", email="faisal.dosani@capitalone.com" }
 ]
 license = {text = "Apache Software License"}
-dependencies = ["pandas<=2.2.3,>=0.25.0", "numpy<=2.1.2,>=1.22.0", "ordered-set<=4.1.0,>=4.0.2", "fugue<=0.9.1,>=0.8.7", "polars<=1.7.0,>=0.20.4"]
+dependencies = ["pandas<=2.2.3,>=0.25.0", "numpy<=2.1.2,>=1.22.0", "ordered-set<=4.1.0,>=4.0.2", "fugue<=0.9.1,>=0.8.7", "polars<=1.12.0,>=0.20.4"]
 requires-python = ">=3.9.0"
 classifiers = [
     "Intended Audience :: Developers",

tests/test_polars.py

@@ -387,7 +387,7 @@ def test_compare_df_setter_bad():
     with raises(ValueError, match="df1 must have all columns from join_columns"):
         PolarsCompare(df, df.clone(), ["b"])
     with raises(
-        DuplicateError, match="column with name 'a' has more than one occurrences"
+        DuplicateError, match="column with name 'a' has more than one occurrence"
     ):
         PolarsCompare(df_same_col_names, df_same_col_names.clone(), ["a"])
     assert PolarsCompare(df_dupe, df_dupe.clone(), ["a", "b"]).df1.equals(df_dupe)
@@ -419,7 +419,7 @@ def test_compare_df_setter_bad_index():
     with raises(TypeError, match="df1 must be a Polars DataFrame"):
         PolarsCompare("a", "a", join_columns="a")
     with raises(
-        DuplicateError, match="column with name 'a' has more than one occurrences"
+        DuplicateError, match="column with name 'a' has more than one occurrence"
     ):
         PolarsCompare(df, df.clone(), join_columns="a")