PERF: slicing

pandas/_libs/internals.pyx

@@ -831,7 +831,7 @@ cdef class BlockManager:
     # -------------------------------------------------------------------
     # Indexing
 
-    cdef BlockManager _get_index_slice(self, slobj):
+    cdef BlockManager _get_index_slice(self, slice slobj):
         cdef:
             SharedBlock blk, nb
             BlockManager mgr

pandas/_libs/lib.pyi

@@ -47,6 +47,7 @@ def is_decimal(val: object) -> TypeGuard[Decimal]: ...
 def is_complex(val: object) -> TypeGuard[complex]: ...
 def is_bool(val: object) -> TypeGuard[bool | np.bool_]: ...
 def is_integer(val: object) -> TypeGuard[int | np.integer]: ...
+def is_int_or_none(obj) -> bool: ...
 def is_float(val: object) -> TypeGuard[float]: ...
 def is_interval_array(values: np.ndarray) -> bool: ...
 def is_datetime64_array(values: np.ndarray) -> bool: ...

pandas/_libs/lib.pyx

@@ -1057,6 +1057,17 @@ def is_integer(obj: object) -> bool:
     return util.is_integer_object(obj)
 
 
+def is_int_or_none(obj) -> bool:
+    """
+    Return True if given object is integer or None.
+
+    Returns
+    -------
+    bool
+    """
+    return obj is None or util.is_integer_object(obj)
+
+
 def is_bool(obj: object) -> bool:
     """
     Return True if given object is boolean.

pandas/core/generic.py

@@ -6009,10 +6009,10 @@ def __finalize__(self, other, method: str | None = None, **kwargs) -> Self:
                stable across pandas releases.
         """
         if isinstance(other, NDFrame):
-            for name in other.attrs:
+            for name in other._attrs:
                 self.attrs[name] = other.attrs[name]
 
-            self.flags.allows_duplicate_labels = other.flags.allows_duplicate_labels
+            self._flags.allows_duplicate_labels = other._flags.allows_duplicate_labels
             # For subclasses using _metadata.
             for name in set(self._metadata) & set(other._metadata):
                 assert isinstance(name, str)

pandas/core/indexers/utils.py

@@ -10,6 +10,8 @@
 
 import numpy as np
 
+from pandas._libs import lib
+
 from pandas.core.dtypes.common import (
     is_array_like,
     is_bool_dtype,
@@ -50,14 +52,10 @@ def is_valid_positional_slice(slc: slice) -> bool:
     A valid positional slice may also be interpreted as a label-based slice
     depending on the index being sliced.
     """
-
-    def is_int_or_none(val):
-        return val is None or is_integer(val)
-
     return (
-        is_int_or_none(slc.start)
-        and is_int_or_none(slc.stop)
-        and is_int_or_none(slc.step)
+        lib.is_int_or_none(slc.start)
+        and lib.is_int_or_none(slc.stop)
+        and lib.is_int_or_none(slc.step)
     )
 
 

pandas/core/indexes/base.py

@@ -100,7 +100,6 @@
     is_float_dtype,
     is_hashable,
     is_integer,
-    is_integer_dtype,
     is_iterator,
     is_list_like,
     is_numeric_dtype,
@@ -162,7 +161,10 @@
     extract_array,
     sanitize_array,
 )
-from pandas.core.indexers import disallow_ndim_indexing
+from pandas.core.indexers import (
+    disallow_ndim_indexing,
+    is_valid_positional_slice,
+)
 from pandas.core.indexes.frozen import FrozenList
 from pandas.core.missing import clean_reindex_fill_method
 from pandas.core.ops import get_op_result_name
@@ -4072,7 +4074,7 @@ def _validate_positional_slice(self, key: slice) -> None:
         self._validate_indexer("positional", key.stop, "iloc")
         self._validate_indexer("positional", key.step, "iloc")
 
-    def _convert_slice_indexer(self, key: slice, kind: str_t):
+    def _convert_slice_indexer(self, key: slice, kind: Literal["loc", "getitem"]):
         """
         Convert a slice indexer.
 
@@ -4084,7 +4086,6 @@ def _convert_slice_indexer(self, key: slice, kind: str_t):
         key : label of the slice bound
         kind : {'loc', 'getitem'}
         """
-        assert kind in ["loc", "getitem"], kind
 
         # potentially cast the bounds to integers
         start, stop, step = key.start, key.stop, key.step
@@ -4097,22 +4098,14 @@ def _convert_slice_indexer(self, key: slice, kind: str_t):
             return self.slice_indexer(start, stop, step)
 
         # figure out if this is a positional indexer
-        def is_int(v):
-            return v is None or is_integer(v)
-
-        is_index_slice = is_int(start) and is_int(stop) and is_int(step)
-
-        # special case for interval_dtype bc we do not do partial-indexing
-        #  on integer Intervals when slicing
-        # TODO: write this in terms of e.g. should_partial_index?
-        ints_are_positional = self._should_fallback_to_positional or isinstance(
-            self.dtype, IntervalDtype
-        )
-        is_positional = is_index_slice and ints_are_positional
+        is_index_slice = is_valid_positional_slice(key)
 
         if kind == "getitem":
             # called from the getitem slicers, validate that we are in fact integers
-            if is_index_slice or is_integer_dtype(self.dtype):
+            if is_index_slice:
+                # In this case the _validate_indexer checks below are redundant
+                return key
+            elif self.dtype.kind in "iu":
                 # Note: these checks are redundant if we know is_index_slice
                 self._validate_indexer("slice", key.start, "getitem")
                 self._validate_indexer("slice", key.stop, "getitem")
@@ -4121,6 +4114,14 @@ def is_int(v):
 
         # convert the slice to an indexer here
 
+        # special case for interval_dtype bc we do not do partial-indexing
+        #  on integer Intervals when slicing
+        # TODO: write this in terms of e.g. should_partial_index?
+        ints_are_positional = self._should_fallback_to_positional or isinstance(
+            self.dtype, IntervalDtype
+        )
+        is_positional = is_index_slice and ints_are_positional
+
         # if we are mixed and have integers
         if is_positional:
             try:
@@ -4152,7 +4153,7 @@ def is_int(v):
     @final
     def _raise_invalid_indexer(
         self,
-        form: str_t,
+        form: Literal["slice", "positional"],
         key,
         reraise: lib.NoDefault | None | Exception = lib.no_default,
     ) -> None:
@@ -6380,14 +6381,17 @@ def _maybe_cast_listlike_indexer(self, target) -> Index:
         return ensure_index(target)
 
     @final
-    def _validate_indexer(self, form: str_t, key, kind: str_t) -> None:
+    def _validate_indexer(
+        self,
+        form: Literal["positional", "slice"],
+        key,
+        kind: Literal["getitem", "iloc"],
+    ) -> None:
         """
         If we are positional indexer, validate that we have appropriate
         typed bounds must be an integer.
         """
-        assert kind in ["getitem", "iloc"]
-
-        if key is not None and not is_integer(key):
+        if not lib.is_int_or_none(key):
             self._raise_invalid_indexer(form, key)
 
     def _maybe_cast_slice_bound(self, label, side: str_t):

pandas/core/indexes/interval.py

@@ -784,7 +784,7 @@ def _index_as_unique(self) -> bool:
         "cannot handle overlapping indices; use IntervalIndex.get_indexer_non_unique"
     )
 
-    def _convert_slice_indexer(self, key: slice, kind: str):
+    def _convert_slice_indexer(self, key: slice, kind: Literal["loc", "getitem"]):
         if not (key.step is None or key.step == 1):
             # GH#31658 if label-based, we require step == 1,
             #  if positional, we disallow float start/stop

pandas/core/indexes/range.py

@@ -54,6 +54,7 @@
         npt,
     )
 _empty_range = range(0)
+_dtype_int64 = np.dtype(np.int64)
 
 
 class RangeIndex(Index):
@@ -309,7 +310,7 @@ def memory_usage(self, deep: bool = False) -> int:
 
     @property
     def dtype(self) -> np.dtype:
-        return np.dtype(np.int64)
+        return _dtype_int64
 
     @property
     def is_unique(self) -> bool: