REF: remove _get_attributes_dict

pandas/core/indexes/base.py

@@ -728,13 +728,6 @@ def _format_duplicate_message(self) -> DataFrame:
     # --------------------------------------------------------------------
     # Index Internals Methods
 
-    @final
-    def _get_attributes_dict(self) -> dict[str_t, Any]:
-        """
-        Return an attributes dict for my class.
-        """
-        return {k: getattr(self, k, None) for k in self._attributes}
-
     def _shallow_copy(self: _IndexT, values, name: Hashable = no_default) -> _IndexT:
         """
         Create a new Index with the same class as the caller, don't copy the
@@ -859,9 +852,7 @@ def __array_wrap__(self, result, context=None):
         if is_bool_dtype(result) or lib.is_scalar(result) or np.ndim(result) > 1:
             return result
 
-        attrs = self._get_attributes_dict()
-        attrs.pop("freq", None)  # For DatetimeIndex/TimedeltaIndex
-        return Index(result, **attrs)
+        return Index(result, name=self.name)
 
     @cache_readonly
     def dtype(self) -> DtypeObj:
@@ -2493,8 +2484,7 @@ def _is_multi(self) -> bool:
     # Pickle Methods
 
     def __reduce__(self):
-        d = {"data": self._data}
-        d.update(self._get_attributes_dict())
+        d = {"data": self._data, "name": self.name}
         return _new_Index, (type(self), d), None
 
     # --------------------------------------------------------------------
@@ -5820,29 +5810,29 @@ def map(self, mapper, na_action=None):
 
         new_values = self._map_values(mapper, na_action=na_action)
 
-        attributes = self._get_attributes_dict()
-
         # we can return a MultiIndex
         if new_values.size and isinstance(new_values[0], tuple):
             if isinstance(self, MultiIndex):
                 names = self.names
-            elif attributes.get("name"):
-                names = [attributes.get("name")] * len(new_values[0])
+            elif self.name:
+                names = [self.name] * len(new_values[0])
             else:
                 names = None
             return MultiIndex.from_tuples(new_values, names=names)
 
-        attributes["copy"] = False
+        dtype = None
         if not new_values.size:
             # empty
-            attributes["dtype"] = self.dtype
+            dtype = self.dtype
 
         if self._is_backward_compat_public_numeric_index and is_numeric_dtype(
             new_values.dtype
         ):
-            return self._constructor(new_values, **attributes)
+            return self._constructor(
+                new_values, dtype=dtype, copy=False, name=self.name
+            )
 
-        return Index._with_infer(new_values, **attributes)
+        return Index._with_infer(new_values, dtype=dtype, copy=False, name=self.name)
 
     # TODO: De-duplicate with map, xref GH#32349
     @final

pandas/core/indexes/category.py

@@ -194,8 +194,6 @@ def _engine_type(self):
             np.int64: libindex.Int64Engine,
         }[self.codes.dtype.type]
 
-    _attributes = ["name"]
-
     # --------------------------------------------------------------------
     # Constructors
 

pandas/core/indexes/datetimes.py

@@ -357,12 +357,7 @@ def _is_dates_only(self) -> bool:
         return self.tz is None and is_dates_only(self._values)  # type: ignore[arg-type]
 
     def __reduce__(self):
-
-        # we use a special reduce here because we need
-        # to simply set the .tz (and not reinterpret it)
-
-        d = {"data": self._data}
-        d.update(self._get_attributes_dict())
+        d = {"data": self._data, "name": self.name}
         return _new_DatetimeIndex, (type(self), d), None
 
     def _is_comparable_dtype(self, dtype: DtypeObj) -> bool:

pandas/core/indexes/interval.py

@@ -354,8 +354,12 @@ def _multiindex(self) -> MultiIndex:
         return MultiIndex.from_arrays([self.left, self.right], names=["left", "right"])
 
     def __reduce__(self):
-        d = {"left": self.left, "right": self.right, "closed": self.closed}
-        d.update(self._get_attributes_dict())
+        d = {
+            "left": self.left,
+            "right": self.right,
+            "closed": self.closed,
+            "name": self.name,
+        }
         return _new_IntervalIndex, (type(self), d), None
 
     @property

pandas/core/indexes/period.py

@@ -148,7 +148,6 @@ class PeriodIndex(DatetimeIndexOpsMixin):
     """
 
     _typ = "periodindex"
-    _attributes = ["name"]
 
     _data: PeriodArray
     freq: BaseOffset

pandas/core/indexes/range.py

@@ -206,7 +206,7 @@ def _get_data_as_items(self):
         return [("start", rng.start), ("stop", rng.stop), ("step", rng.step)]
 
     def __reduce__(self):
-        d = self._get_attributes_dict()
+        d = {"name": self.name}
         d.update(dict(self._get_data_as_items()))
         return ibase._new_Index, (type(self), d), None
 
@@ -913,7 +913,6 @@ def _arith_method(self, other, op):
 
         # TODO: if other is a RangeIndex we may have more efficient options
         other = extract_array(other, extract_numpy=True, extract_range=True)
-        attrs = self._get_attributes_dict()
 
         left, right = self, other
 
@@ -935,7 +934,7 @@ def _arith_method(self, other, op):
                 rstart = op(left.start, right)
                 rstop = op(left.stop, right)
 
-            result = type(self)(rstart, rstop, rstep, **attrs)
+            result = type(self)(rstart, rstop, rstep, name=self.name)
 
             # for compat with numpy / Int64Index
             # even if we can represent as a RangeIndex, return