Clean up merge glitches

Some merge resolutions stepped on my changes.  Also run black over everything.  Hopefully fixed now.

Signed-off-by: Michael Tiemann <72577720+MichaelTiemannOSC@users.noreply.github.com>

Author: MichaelTiemannOSC

pandas/core/arrays/_mixins.py

@@ -517,7 +517,9 @@ def _cast_quantile_result(self, res_values: np.ndarray) -> np.ndarray:
     # numpy-like methods
 
     @classmethod
-    def _empty(cls, shape: Shape, dtype: ExtensionDtype, fill_value: object = None) -> Self:
+    def _empty(
+        cls, shape: Shape, dtype: ExtensionDtype, fill_value: object = None
+    ) -> Self:
         """
         Analogous to np.empty(shape, dtype=dtype)
 

pandas/core/arrays/arrow/array.py

@@ -251,7 +251,14 @@ def __init__(self, values: pa.Array | pa.ChunkedArray) -> None:
         self._dtype = ArrowDtype(self._pa_array.type)
 
     @classmethod
-    def _from_sequence(cls, scalars, *, dtype: Dtype | None = None, fill_value: object | None = None, copy: bool = False):
+    def _from_sequence(
+        cls,
+        scalars,
+        *,
+        dtype: Dtype | None = None,
+        fill_value: object | None = None,
+        copy: bool = False,
+    ):
         """
         Construct a new ExtensionArray from a sequence of scalars.
         """

pandas/core/arrays/base.py

@@ -262,7 +262,14 @@ class ExtensionArray:
     # ------------------------------------------------------------------------
 
     @classmethod
-    def _from_sequence(cls, scalars, *, dtype: Dtype | None = None, fill_value: object = None, copy: bool = False):
+    def _from_sequence(
+        cls,
+        scalars,
+        *,
+        dtype: Dtype | None = None,
+        fill_value: object = None,
+        copy: bool = False,
+    ):
         """
         Construct a new ExtensionArray from a sequence of scalars.
 

pandas/core/arrays/categorical.py

@@ -505,7 +505,12 @@ def _internal_fill_value(self) -> int:
 
     @classmethod
     def _from_sequence(
-            cls, scalars, *, dtype: Dtype | None = None, fill_value: object = None, copy: bool = False
+        cls,
+        scalars,
+        *,
+        dtype: Dtype | None = None,
+        fill_value: object = None,
+        copy: bool = False,
     ) -> Self:
         return cls(scalars, dtype=dtype, copy=copy)
 
@@ -1800,7 +1805,7 @@ def value_counts(self, dropna: bool = True) -> Series:
     # "ExtensionDtype"
     @classmethod
     def _empty(  # type: ignore[override]
-            cls, shape: Shape, dtype: CategoricalDtype, fill_value: object = None
+        cls, shape: Shape, dtype: CategoricalDtype, fill_value: object = None
     ) -> Self:
         """
         Analogous to np.empty(shape, dtype=dtype)

pandas/core/arrays/datetimes.py

@@ -293,7 +293,9 @@ def _simple_new(  # type: ignore[override]
         return result
 
     @classmethod
-    def _from_sequence(cls, scalars, *, dtype=None, fill_value: object = None, copy: bool = False):
+    def _from_sequence(
+        cls, scalars, *, dtype=None, fill_value: object = None, copy: bool = False
+    ):
         return cls._from_sequence_not_strict(scalars, dtype=dtype, copy=copy)
 
     @classmethod

pandas/core/arrays/masked.py

@@ -145,7 +145,9 @@ def __init__(
         self._mask = mask
 
     @classmethod
-    def _from_sequence(cls, scalars, *, dtype=None, fill_value: object = None, copy: bool = False) -> Self:
+    def _from_sequence(
+        cls, scalars, *, dtype=None, fill_value: object = None, copy: bool = False
+    ) -> Self:
         values, mask = cls._coerce_to_array(scalars, dtype=dtype, copy=copy)
         return cls(values, mask)
 

pandas/core/arrays/numpy_.py

@@ -117,7 +117,12 @@ def __init__(
 
     @classmethod
     def _from_sequence(
-        cls, scalars, *, dtype: Dtype | None = None, fill_value: object = None, copy: bool = False
+        cls,
+        scalars,
+        *,
+        dtype: Dtype | None = None,
+        fill_value: object = None,
+        copy: bool = False,
     ) -> NumpyExtensionArray:
         if isinstance(dtype, NumpyEADtype):
             dtype = dtype._dtype

pandas/core/arrays/sparse/array.py

@@ -583,7 +583,14 @@ def __setitem__(self, key, value) -> None:
         raise TypeError(msg)
 
     @classmethod
-    def _from_sequence(cls, scalars, *, dtype: Dtype | None = None, fill_value: object | None = None, copy: bool = False):
+    def _from_sequence(
+        cls,
+        scalars,
+        *,
+        dtype: Dtype | None = None,
+        fill_value: object | None = None,
+        copy: bool = False,
+    ):
         return cls(scalars, dtype=dtype)
 
     @classmethod

pandas/core/arrays/string_.py

@@ -340,7 +340,14 @@ def _validate(self):
             lib.convert_nans_to_NA(self._ndarray)
 
     @classmethod
-    def _from_sequence(cls, scalars, *, dtype: Dtype | None = None, fill_value: object | None = None, copy: bool = False):
+    def _from_sequence(
+        cls,
+        scalars,
+        *,
+        dtype: Dtype | None = None,
+        fill_value: object | None = None,
+        copy: bool = False,
+    ):
         if dtype and not (isinstance(dtype, str) and dtype == "string"):
             dtype = pandas_dtype(dtype)
             assert isinstance(dtype, StringDtype) and dtype.storage == "python"
@@ -377,7 +384,7 @@ def _from_sequence_of_strings(
         return cls._from_sequence(strings, dtype=dtype, copy=copy)
 
     @classmethod
-    def _empty(cls, shape, dtype, fill_value = None) -> StringArray:
+    def _empty(cls, shape, dtype, fill_value=None) -> StringArray:
         values = np.empty(shape, dtype=object)
         values[:] = libmissing.NA
         return cls(values).astype(dtype, copy=False)

pandas/core/arrays/string_arrow.py

@@ -137,7 +137,13 @@ def __len__(self) -> int:
         return len(self._pa_array)
 
     @classmethod
-    def _from_sequence(cls, scalars, dtype: Dtype | None = None, fill_value: object | None = None, copy: bool = False):
+    def _from_sequence(
+        cls,
+        scalars,
+        dtype: Dtype | None = None,
+        fill_value: object | None = None,
+        copy: bool = False,
+    ):
         from pandas.core.arrays.masked import BaseMaskedArray
 
         _chk_pyarrow_available()

pandas/core/arrays/timedeltas.py

@@ -229,7 +229,9 @@ def _simple_new(  # type: ignore[override]
         return result
 
     @classmethod
-    def _from_sequence(cls, data, *, dtype=None, fill_value: object = None, copy: bool = False) -> Self:
+    def _from_sequence(
+        cls, data, *, dtype=None, fill_value: object = None, copy: bool = False
+    ) -> Self:
         if dtype:
             dtype = _validate_td64_dtype(dtype)
 

pandas/tests/extension/decimal/test_decimal.py

@@ -67,7 +67,7 @@ def data_for_grouping():
 
 class TestDecimalArray(base.ExtensionTests):
     def _get_expected_exception(
-        self, op_name: str, obj, other
+        self, op_name: str, obj, other, request
     ) -> type[Exception] | None:
         return None
 
@@ -108,7 +108,7 @@ def test_compare_array(self, data, comparison_op):
         other = pd.Series(data) * [decimal.Decimal(pow(2.0, i)) for i in alter]
         self._compare_other(ser, data, comparison_op, other)
 
-    def test_arith_series_with_array(self, data, all_arithmetic_operators):
+    def test_arith_series_with_array(self, data, all_arithmetic_operators, request):
         op_name = all_arithmetic_operators
         ser = pd.Series(data)
 
@@ -120,13 +120,13 @@ def test_arith_series_with_array(self, data, all_arithmetic_operators):
 
         # Decimal supports ops with int, but not float
         other = pd.Series([int(d * 100) for d in data])
-        self.check_opname(ser, op_name, other)
+        self.check_opname(ser, op_name, other, request)
 
         if "mod" not in op_name:
-            self.check_opname(ser, op_name, ser * 2)
+            self.check_opname(ser, op_name, ser * 2, request)
 
-        self.check_opname(ser, op_name, 0)
-        self.check_opname(ser, op_name, 5)
+        self.check_opname(ser, op_name, 0, request)
+        self.check_opname(ser, op_name, 5, request)
         context.traps[decimal.DivisionByZero] = divbyzerotrap
         context.traps[decimal.InvalidOperation] = invalidoptrap
 

pandas/tests/extension/test_masked.py

@@ -160,7 +160,7 @@ def data_for_grouping(dtype):
 
 
 class TestMaskedArrays(base.ExtensionTests):
-    def _get_expected_exception(self, op_name, obj, other):
+    def _get_expected_exception(self, op_name, obj, other, request):
         try:
             dtype = tm.get_dtype(obj)
         except AttributeError:

pandas/tests/extension/test_numpy.py

@@ -315,6 +315,7 @@ def _get_expected_exception(
                         pytest.mark.xfail(
                             raises=TypeError,
                             reason=f"{marked_reason} does not support {op_name}",
+                            strict=False,
                         )
                     )
                     return TypeError