TYP: ndim is consistently a property

pandas/core/arrays/datetimes.py

@@ -193,12 +193,15 @@ class DatetimeArray(dtl.TimelikeOps, dtl.DatelikeOps):
     """
 
     _typ = "datetimearray"
-    _scalar_type = Timestamp
     _internal_fill_value = np.datetime64("NaT", "ns")
     _recognized_scalars = (datetime, np.datetime64)
     _is_recognized_dtype = is_datetime64_any_dtype
     _infer_matches = ("datetime", "datetime64", "date")
 
+    @property
+    def _scalar_type(self) -> type[Timestamp]:
+        return Timestamp
+
     # define my properties & methods for delegation
     _bool_ops: list[str] = [
         "is_month_start",

pandas/core/arrays/interval.py

@@ -8,6 +8,7 @@
 import textwrap
 from typing import (
     TYPE_CHECKING,
+    Literal,
     Sequence,
     TypeVar,
     Union,
@@ -204,10 +205,13 @@
     }
 )
 class IntervalArray(IntervalMixin, ExtensionArray):
-    ndim = 1
     can_hold_na = True
     _na_value = _fill_value = np.nan
 
+    @property
+    def ndim(self) -> Literal[1]:
+        return 1
+
     # To make mypy recognize the fields
     _left: np.ndarray
     _right: np.ndarray

pandas/core/arrays/period.py

@@ -167,12 +167,15 @@ class PeriodArray(dtl.DatelikeOps, libperiod.PeriodMixin):
     # array priority higher than numpy scalars
     __array_priority__ = 1000
     _typ = "periodarray"  # ABCPeriodArray
-    _scalar_type = Period
     _internal_fill_value = np.int64(iNaT)
     _recognized_scalars = (Period,)
     _is_recognized_dtype = is_period_dtype
     _infer_matches = ("period",)
 
+    @property
+    def _scalar_type(self) -> type[Period]:
+        return Period
+
     # Names others delegate to us
     _other_ops: list[str] = []
     _bool_ops: list[str] = ["is_leap_year"]

pandas/core/arrays/timedeltas.py

@@ -119,12 +119,15 @@ class TimedeltaArray(dtl.TimelikeOps):
     """
 
     _typ = "timedeltaarray"
-    _scalar_type = Timedelta
     _internal_fill_value = np.timedelta64("NaT", "ns")
     _recognized_scalars = (timedelta, np.timedelta64, Tick)
     _is_recognized_dtype = is_timedelta64_dtype
     _infer_matches = ("timedelta", "timedelta64")
 
+    @property
+    def _scalar_type(self) -> type[Timedelta]:
+        return Timedelta
+
     __array_priority__ = 1000
     # define my properties & methods for delegation
     _other_ops: list[str] = []

pandas/core/base.py

@@ -318,7 +318,7 @@ def __len__(self) -> int:
         raise AbstractMethodError(self)
 
     @property
-    def ndim(self) -> int:
+    def ndim(self) -> Literal[1]:
         """
         Number of dimensions of the underlying data, by definition 1.
         """

pandas/core/internals/array_manager.py

@@ -8,6 +8,7 @@
     Any,
     Callable,
     Hashable,
+    Literal,
     TypeVar,
 )
 
@@ -704,7 +705,9 @@ def _equal_values(self, other) -> bool:
 
 
 class ArrayManager(BaseArrayManager):
-    ndim = 2
+    @property
+    def ndim(self) -> Literal[2]:
+        return 2
 
     def __init__(
         self,
@@ -1191,7 +1194,9 @@ class SingleArrayManager(BaseArrayManager, SingleDataManager):
     arrays: list[np.ndarray | ExtensionArray]
     _axes: list[Index]
 
-    ndim = 1
+    @property
+    def ndim(self) -> Literal[1]:
+        return 1
 
     def __init__(
         self,

pandas/core/internals/base.py

@@ -5,6 +5,7 @@
 from __future__ import annotations
 
 from typing import (
+    Literal,
     TypeVar,
     final,
 )
@@ -155,7 +156,9 @@ def _consolidate_inplace(self) -> None:
 
 
 class SingleDataManager(DataManager):
-    ndim = 1
+    @property
+    def ndim(self) -> Literal[1]:
+        return 1
 
     @final
     @property

pandas/core/internals/managers.py

@@ -5,6 +5,7 @@
     Any,
     Callable,
     Hashable,
+    Literal,
     Sequence,
     TypeVar,
     cast,
@@ -142,7 +143,10 @@ class BaseBlockManager(DataManager):
     blocks: tuple[Block, ...]
     axes: list[Index]
 
-    ndim: int
+    @property
+    def ndim(self) -> int:
+        raise NotImplementedError
+
     _known_consolidated: bool
     _is_consolidated: bool
 
@@ -1678,7 +1682,10 @@ def _consolidate_inplace(self) -> None:
 class SingleBlockManager(BaseBlockManager, SingleDataManager):
     """manage a single block with"""
 
-    ndim = 1
+    @property
+    def ndim(self) -> Literal[1]:
+        return 1
+
     _is_consolidated = True
     _known_consolidated = True
     __slots__ = ()

pandas/tests/arrays/test_datetimelike.py

@@ -564,7 +564,7 @@ def test_shift_fill_int_deprecated(self):
 
         expected = arr.copy()
         if self.array_cls is PeriodArray:
-            fill_val = PeriodArray._scalar_type._from_ordinal(1, freq=arr.freq)
+            fill_val = arr._scalar_type._from_ordinal(1, freq=arr.freq)
         else:
             fill_val = arr._scalar_type(1)
         expected[0] = fill_val

pyright_reportGeneralTypeIssues.json

@@ -61,7 +61,6 @@
         "pandas/core/indexing.py",
         "pandas/core/internals/api.py",
         "pandas/core/internals/array_manager.py",
-        "pandas/core/internals/base.py",
         "pandas/core/internals/blocks.py",
         "pandas/core/internals/concat.py",
         "pandas/core/internals/construction.py",