Fixes default data quality pd series type check

This was not handling the new pandas types.
This seems to fix that, while also updating the example
to no log warnings.

examples/data_quality/simple/feature_logic.py

@@ -82,25 +82,25 @@ def seasons_encoded__dask(seasons: pd.Series) -> pd.DataFrame:
     return df
 
 
-@check_output(data_type=np.uint8, values_in=[0, 1], allow_nans=False)
+@check_output(data_type=np.bool_, values_in=[0, 1], allow_nans=False)
 def seasons_1(seasons_encoded: pd.DataFrame) -> pd.Series:
     """Returns column seasons_1"""
     return seasons_encoded["seasons_1"]
 
 
-@check_output(data_type=np.uint8, values_in=[0, 1], allow_nans=False)
+@check_output(data_type=np.bool_, values_in=[0, 1], allow_nans=False)
 def seasons_2(seasons_encoded: pd.DataFrame) -> pd.Series:
     """Returns column seasons_2"""
     return seasons_encoded["seasons_2"]
 
 
-@check_output(data_type=np.uint8, values_in=[0, 1], allow_nans=False)
+@check_output(data_type=np.bool_, values_in=[0, 1], allow_nans=False)
 def seasons_3(seasons_encoded: pd.DataFrame) -> pd.Series:
     """Returns column seasons_3"""
     return seasons_encoded["seasons_3"]
 
 
-@check_output(data_type=np.uint8, values_in=[0, 1], allow_nans=False)
+@check_output(data_type=np.bool_, values_in=[0, 1], allow_nans=False)
 def seasons_4(seasons_encoded: pd.DataFrame) -> pd.Series:
     """Returns column seasons_4"""
     return seasons_encoded["seasons_4"]
@@ -136,31 +136,31 @@ def day_of_week_encoded__dask(day_of_the_week: pd.Series) -> pd.DataFrame:
     return df
 
 
-@check_output(data_type=np.uint8, values_in=[0, 1], allow_nans=False)
+@check_output(data_type=np.bool_, values_in=[0, 1], allow_nans=False)
 def day_of_the_week_2(day_of_week_encoded: pd.DataFrame) -> pd.Series:
     """Pulls out the day_of_the_week_2 column."""
     return day_of_week_encoded["day_of_the_week_2"]
 
 
-@check_output(data_type=np.uint8, values_in=[0, 1], allow_nans=False)
+@check_output(data_type=np.bool_, values_in=[0, 1], allow_nans=False)
 def day_of_the_week_3(day_of_week_encoded: pd.DataFrame) -> pd.Series:
     """Pulls out the day_of_the_week_3 column."""
     return day_of_week_encoded["day_of_the_week_3"]
 
 
-@check_output(data_type=np.uint8, values_in=[0, 1], allow_nans=False)
+@check_output(data_type=np.bool_, values_in=[0, 1], allow_nans=False)
 def day_of_the_week_4(day_of_week_encoded: pd.DataFrame) -> pd.Series:
     """Pulls out the day_of_the_week_4 column."""
     return day_of_week_encoded["day_of_the_week_4"]
 
 
-@check_output(data_type=np.uint8, values_in=[0, 1], allow_nans=False)
+@check_output(data_type=np.bool_, values_in=[0, 1], allow_nans=False)
 def day_of_the_week_5(day_of_week_encoded: pd.DataFrame) -> pd.Series:
     """Pulls out the day_of_the_week_5 column."""
     return day_of_week_encoded["day_of_the_week_5"]
 
 
-@check_output(data_type=np.uint8, values_in=[0, 1], allow_nans=False)
+@check_output(data_type=np.bool_, values_in=[0, 1], allow_nans=False)
 def day_of_the_week_6(day_of_week_encoded: pd.DataFrame) -> pd.Series:
     """Pulls out the day_of_the_week_6 column."""
     return day_of_week_encoded["day_of_the_week_6"]

hamilton/data_quality/default_validators.py

@@ -259,6 +259,8 @@ def description(self) -> str:
 
     def validate(self, data: pd.Series) -> base.ValidationResult:
         dtype = data.dtype
+        if hasattr(dtype, "type"):
+            dtype = dtype.type
         passes = np.issubdtype(dtype, self.datatype)
         return base.ValidationResult(
             passes=passes,

tests/test_default_data_quality.py

@@ -171,6 +171,12 @@ def test_resolve_default_validators_error(output_type, kwargs, importance):
             pd.Series(["hello", "goodbye"]),
             True,
         ),
+        (
+            default_validators.DataTypeValidatorPandasSeries,
+            np.float64,
+            pd.Series([2.3, 4.5, 6.6], dtype=pd.Float64Dtype()),
+            True,
+        ),
         (
             default_validators.DataTypeValidatorPandasSeries,
             numpy.dtype("object"),