🦉 Updates from OwlBot post-processor

See https://github.com/googleapis/repo-automation-bots/blob/main/packages/owl-bot/README.md

Author: gcf-owl-bot[bot]

Diff for: db_dtypes/json.py

@@ -34,6 +34,7 @@
     "ge": pyarrow.compute.greater_equal,
 }
 
+
 @pd.api.extensions.register_extension_dtype
 class JSONDtype(pd.api.extensions.ExtensionDtype):
     """Extension dtype for BigQuery JSON data."""
@@ -255,28 +256,24 @@ def _reduce(
             raise TypeError("JSONArray does not support min/max reducntion.")
         super()._reduce(name, skipna=skipna, keepdims=keepdims, **kwargs)
 
-    def __array__(
-        self, dtype = None, copy = None
-    ) -> np.ndarray:
+    def __array__(self, dtype=None, copy=None) -> np.ndarray:
         """Correctly construct numpy arrays when passed to `np.asarray()`."""
         return self.to_numpy(dtype=dtype)
 
-    def to_numpy(self, dtype = None, copy = False, na_value = pd.NA) -> np.ndarray:
+    def to_numpy(self, dtype=None, copy=False, na_value=pd.NA) -> np.ndarray:
         dtype, na_value = self._to_numpy_dtype_inference(dtype, na_value, self._hasna)
         pa_type = self._pa_array.type
         if not self._hasna or pd.isna(na_value) or pa.types.is_null(pa_type):
             data = self
         else:
             data = self.fillna(na_value)
         result = np.array(list(data), dtype=dtype)
-        
+
         if data._hasna:
             result[data.isna()] = na_value
         return result
 
-    def _to_numpy_dtype_inference(
-        self, dtype, na_value, hasna
-    ):
+    def _to_numpy_dtype_inference(self, dtype, na_value, hasna):
         if dtype is not None:
             dtype = np.dtype(dtype)
 
@@ -290,4 +287,4 @@ def _to_numpy_dtype_inference(
             na_value = np.timedelta64("nat")
         else:
             na_value = self.dtype.na_value
-        return dtype, na_value
+        return dtype, na_value

Diff for: tests/compliance/json/test_json_compliance.py

@@ -251,7 +251,6 @@ def test_setitem_mask_boolean_array_with_na(self, data, box_in_series):
         super().test_setitem_mask_boolean_array_with_na(data, box_in_series)
 
     @pytest.mark.parametrize("setter", ["loc", "iloc"])
-    
     @pytest.mark.xfail(reason="TODO: open an issue for ArrowExtentionArray")
     def test_setitem_scalar(self, data, setter):
         super().test_setitem_scalar(data, setter)