CLN: assorted (#52820)

* CLN: assorted

* typo fixup

Author: jbrockmendel

pandas/_libs/tslibs/conversion.pyx

@@ -61,7 +61,6 @@ from pandas._libs.tslibs.nattype cimport (
     c_nat_strings as nat_strings,
 )
 from pandas._libs.tslibs.parsing cimport parse_datetime_string
-from pandas._libs.tslibs.timestamps cimport _Timestamp
 from pandas._libs.tslibs.timezones cimport (
     get_utcoffset,
     is_utc,
@@ -761,7 +760,7 @@ cdef int64_t parse_pydatetime(
             _ts.ensure_reso(NPY_FR_ns)
             result = _ts.value
     else:
-        if isinstance(val, _Timestamp):
+        if isinstance(val, ABCTimestamp):
             result = val.as_unit("ns")._value
         else:
             result = pydatetime_to_dt64(val, dts)

pandas/_libs/tslibs/timestamps.pyx

@@ -22,7 +22,7 @@ from numpy cimport (
 
 cnp.import_array()
 
-from cpython.datetime cimport (  # alias bc `tzinfo` is a kwarg below
+from cpython.datetime cimport (  # alias tzinfo_type bc `tzinfo` is a kwarg below
     PyDate_Check,
     PyDateTime_Check,
     PyDelta_Check,

pandas/_libs/tslibs/util.pxd

@@ -10,6 +10,7 @@ cdef extern from "Python.h":
     bint PyComplex_Check(object obj) nogil
     bint PyObject_TypeCheck(object obj, PyTypeObject* type) nogil
 
+    # TODO(cython3): cimport this, xref GH#49670
     # Note that following functions can potentially raise an exception,
     # thus they cannot be declared 'nogil'. Also PyUnicode_AsUTF8AndSize() can
     # potentially allocate memory inside in unlikely case of when underlying

pandas/core/computation/align.py

@@ -133,9 +133,8 @@ def _align_core(terms):
                         w, category=PerformanceWarning, stacklevel=find_stack_level()
                     )
 
-                f = partial(ti.reindex, reindexer, axis=axis, copy=False)
-
-                terms[i].update(f())
+                obj = ti.reindex(reindexer, axis=axis, copy=False)
+                terms[i].update(obj)
 
         terms[i].update(terms[i].value.values)
 

pandas/core/dtypes/cast.py

@@ -50,7 +50,6 @@
     ensure_str,
     is_bool,
     is_complex,
-    is_extension_array_dtype,
     is_float,
     is_integer,
     is_object_dtype,
@@ -903,7 +902,8 @@ def infer_dtype_from_array(
     if not is_list_like(arr):
         raise TypeError("'arr' must be list-like")
 
-    if pandas_dtype and is_extension_array_dtype(arr):
+    arr_dtype = getattr(arr, "dtype", None)
+    if pandas_dtype and isinstance(arr_dtype, ExtensionDtype):
         return arr.dtype, arr
 
     elif isinstance(arr, ABCSeries):

pandas/core/dtypes/missing.py

@@ -26,7 +26,6 @@
     TD64NS_DTYPE,
     ensure_object,
     is_dtype_equal,
-    is_extension_array_dtype,
     is_scalar,
     is_string_or_object_np_dtype,
 )
@@ -56,6 +55,7 @@
         npt,
     )
 
+    from pandas import Series
     from pandas.core.indexes.base import Index
 
 
@@ -642,11 +642,11 @@ def na_value_for_dtype(dtype: DtypeObj, compat: bool = True):
     return np.nan
 
 
-def remove_na_arraylike(arr):
+def remove_na_arraylike(arr: Series | Index | np.ndarray):
     """
     Return array-like containing only true/non-NaN values, possibly empty.
     """
-    if is_extension_array_dtype(arr):
+    if isinstance(arr.dtype, ExtensionDtype):
         return arr[notna(arr)]
     else:
         return arr[notna(np.asarray(arr))]

pandas/core/generic.py

@@ -590,6 +590,7 @@ def _get_cleaned_column_resolvers(self) -> dict[Hashable, Series]:
             clean_column_name(k): v for k, v in self.items() if not isinstance(k, int)
         }
 
+    @final
     @property
     def _info_axis(self) -> Index:
         return getattr(self, self._info_axis_name)
@@ -969,6 +970,7 @@ def squeeze(self, axis: Axis | None = None):
     # ----------------------------------------------------------------------
     # Rename
 
+    @final
     def _rename(
         self,
         mapper: Renamer | None = None,
@@ -3476,6 +3478,7 @@ def _wrap(x, alt_format_):
             render_kwargs=render_kwargs_,
         )
 
+    @final
     def _to_latex_via_styler(
         self,
         buf=None,
@@ -4293,6 +4296,7 @@ def _check_setitem_copy(self, t: str = "setting", force: bool_t = False):
         if value == "warn":
             warnings.warn(t, SettingWithCopyWarning, stacklevel=find_stack_level())
 
+    @final
     def __delitem__(self, key) -> None:
         """
         Delete item
@@ -6069,6 +6073,7 @@ def __finalize__(self, other, method: str | None = None, **kwargs) -> Self:
 
         return self
 
+    @final
     def __getattr__(self, name: str):
         """
         After regular attribute access, try looking up the name
@@ -6085,6 +6090,7 @@ def __getattr__(self, name: str):
             return self[name]
         return object.__getattribute__(self, name)
 
+    @final
     def __setattr__(self, name: str, value) -> None:
         """
         After regular attribute access, try setting the name
@@ -6255,6 +6261,7 @@ def dtypes(self):
         data = self._mgr.get_dtypes()
         return self._constructor_sliced(data, index=self._info_axis, dtype=np.object_)
 
+    @final
     def astype(
         self, dtype, copy: bool_t | None = None, errors: IgnoreRaise = "raise"
     ) -> Self:
@@ -7128,6 +7135,7 @@ def ffill(
     ) -> Self | None:
         ...
 
+    @final
     @doc(klass=_shared_doc_kwargs["klass"])
     def ffill(
         self,
@@ -7149,6 +7157,7 @@ def ffill(
             method="ffill", axis=axis, inplace=inplace, limit=limit, downcast=downcast
         )
 
+    @final
     @doc(klass=_shared_doc_kwargs["klass"])
     def pad(
         self,
@@ -7211,6 +7220,7 @@ def bfill(
     ) -> Self | None:
         ...
 
+    @final
     @doc(klass=_shared_doc_kwargs["klass"])
     def bfill(
         self,
@@ -7232,6 +7242,7 @@ def bfill(
             method="bfill", axis=axis, inplace=inplace, limit=limit, downcast=downcast
         )
 
+    @final
     @doc(klass=_shared_doc_kwargs["klass"])
     def backfill(
         self,
@@ -7501,6 +7512,7 @@ def replace(
         else:
             return result.__finalize__(self, method="replace")
 
+    @final
     def interpolate(
         self,
         method: Literal[
@@ -8185,6 +8197,7 @@ def _clip_with_one_bound(self, threshold, method, axis, inplace):
         # GH 40420
         return self.where(subset, threshold, axis=axis, inplace=inplace)
 
+    @final
     def clip(
         self,
         lower=None,
@@ -9996,6 +10009,7 @@ def where(
     ) -> Self | None:
         ...
 
+    @final
     @doc(
         klass=_shared_doc_kwargs["klass"],
         cond="True",
@@ -10188,6 +10202,7 @@ def mask(
     ) -> Self | None:
         ...
 
+    @final
     @doc(
         where,
         klass=_shared_doc_kwargs["klass"],
@@ -10368,6 +10383,7 @@ def shift(
         result = self.set_axis(new_ax, axis=axis)
         return result.__finalize__(self, method="shift")
 
+    @final
     def truncate(
         self,
         before=None,
@@ -11693,46 +11709,56 @@ def _inplace_method(self, other, op) -> Self:
         )
         return self
 
+    @final
     def __iadd__(self, other) -> Self:
         # error: Unsupported left operand type for + ("Type[NDFrame]")
         return self._inplace_method(other, type(self).__add__)  # type: ignore[operator]
 
+    @final
     def __isub__(self, other) -> Self:
         # error: Unsupported left operand type for - ("Type[NDFrame]")
         return self._inplace_method(other, type(self).__sub__)  # type: ignore[operator]
 
+    @final
     def __imul__(self, other) -> Self:
         # error: Unsupported left operand type for * ("Type[NDFrame]")
         return self._inplace_method(other, type(self).__mul__)  # type: ignore[operator]
 
+    @final
     def __itruediv__(self, other) -> Self:
         # error: Unsupported left operand type for / ("Type[NDFrame]")
         return self._inplace_method(
             other, type(self).__truediv__  # type: ignore[operator]
         )
 
+    @final
     def __ifloordiv__(self, other) -> Self:
         # error: Unsupported left operand type for // ("Type[NDFrame]")
         return self._inplace_method(
             other, type(self).__floordiv__  # type: ignore[operator]
         )
 
+    @final
     def __imod__(self, other) -> Self:
         # error: Unsupported left operand type for % ("Type[NDFrame]")
         return self._inplace_method(other, type(self).__mod__)  # type: ignore[operator]
 
+    @final
     def __ipow__(self, other) -> Self:
         # error: Unsupported left operand type for ** ("Type[NDFrame]")
         return self._inplace_method(other, type(self).__pow__)  # type: ignore[operator]
 
+    @final
     def __iand__(self, other) -> Self:
         # error: Unsupported left operand type for & ("Type[NDFrame]")
         return self._inplace_method(other, type(self).__and__)  # type: ignore[operator]
 
+    @final
     def __ior__(self, other) -> Self:
         # error: Unsupported left operand type for | ("Type[NDFrame]")
         return self._inplace_method(other, type(self).__or__)  # type: ignore[operator]
 
+    @final
     def __ixor__(self, other) -> Self:
         # error: Unsupported left operand type for ^ ("Type[NDFrame]")
         return self._inplace_method(other, type(self).__xor__)  # type: ignore[operator]

pandas/core/indexes/base.py

@@ -922,18 +922,20 @@ def __array_ufunc__(self, ufunc: np.ufunc, method: str_t, *inputs, **kwargs):
 
         return self.__array_wrap__(result)
 
+    @final
     def __array_wrap__(self, result, context=None):
         """
         Gets called after a ufunc and other functions e.g. np.split.
         """
         result = lib.item_from_zerodim(result)
         if (
-            (not isinstance(result, Index) and is_bool_dtype(result))
+            (not isinstance(result, Index) and is_bool_dtype(result.dtype))
             or lib.is_scalar(result)
             or np.ndim(result) > 1
         ):
             # exclude Index to avoid warning from is_bool_dtype deprecation;
             #  in the Index case it doesn't matter which path we go down.
+            # reached in plotting tests with e.g. np.nonzero(index)
             return result
 
         return Index(result, name=self.name)

pandas/core/indexes/category.py

@@ -17,6 +17,7 @@
 )
 
 from pandas.core.dtypes.common import is_scalar
+from pandas.core.dtypes.concat import concat_compat
 from pandas.core.dtypes.dtypes import CategoricalDtype
 from pandas.core.dtypes.missing import (
     is_valid_na_for_dtype,
@@ -478,7 +479,6 @@ def _concat(self, to_concat: list[Index], name: Hashable) -> Index:
             )
         except TypeError:
             # not all to_concat elements are among our categories (or NA)
-            from pandas.core.dtypes.concat import concat_compat
 
             res = concat_compat([x._values for x in to_concat])
             return Index(res, name=name)

pandas/core/indexes/interval.py

@@ -113,6 +113,7 @@
 
 
 def _get_next_label(label):
+    # see test_slice_locs_with_ints_and_floats_succeeds
     dtype = getattr(label, "dtype", type(label))
     if isinstance(label, (Timestamp, Timedelta)):
         dtype = "datetime64[ns]"
@@ -129,6 +130,7 @@ def _get_next_label(label):
 
 
 def _get_prev_label(label):
+    # see test_slice_locs_with_ints_and_floats_succeeds
     dtype = getattr(label, "dtype", type(label))
     if isinstance(label, (Timestamp, Timedelta)):
         dtype = "datetime64[ns]"

pandas/core/reshape/melt.py

@@ -10,10 +10,7 @@
 
 from pandas.util._decorators import Appender
 
-from pandas.core.dtypes.common import (
-    is_extension_array_dtype,
-    is_list_like,
-)
+from pandas.core.dtypes.common import is_list_like
 from pandas.core.dtypes.concat import concat_compat
 from pandas.core.dtypes.missing import notna
 
@@ -126,7 +123,8 @@ def melt(
     mdata: dict[Hashable, AnyArrayLike] = {}
     for col in id_vars:
         id_data = frame.pop(col)
-        if is_extension_array_dtype(id_data):
+        if not isinstance(id_data.dtype, np.dtype):
+            # i.e. ExtensionDtype
             if K > 0:
                 mdata[col] = concat([id_data] * K, ignore_index=True)
             else:

pandas/core/reshape/pivot.py

@@ -18,12 +18,12 @@
 
 from pandas.core.dtypes.cast import maybe_downcast_to_dtype
 from pandas.core.dtypes.common import (
-    is_extension_array_dtype,
     is_integer_dtype,
     is_list_like,
     is_nested_list_like,
     is_scalar,
 )
+from pandas.core.dtypes.dtypes import ExtensionDtype
 from pandas.core.dtypes.generic import (
     ABCDataFrame,
     ABCSeries,
@@ -326,7 +326,7 @@ def _add_margins(
     row_names = result.index.names
     # check the result column and leave floats
     for dtype in set(result.dtypes):
-        if is_extension_array_dtype(dtype):
+        if isinstance(dtype, ExtensionDtype):
             # Can hold NA already
             continue