From 695d528112d29a78f020a87fc1da348df15acee7 Mon Sep 17 00:00:00 2001
From: Lawrence Mitchell <lmitchell@nvidia.com>
Date: Fri, 12 May 2023 13:00:27 +0100
Subject: [PATCH 1/3] Remove need for most TypeVar(bound="foo") usage

Now that we support mypy 1.3, we can use the PEP674 Self type
annotation.
---
 python/cudf/cudf/_lib/column.pyi              |  9 ++--
 python/cudf/cudf/core/_base_index.py          | 10 ++---
 python/cudf/cudf/core/buffer/buffer.py        | 11 +++--
 python/cudf/cudf/core/buffer/cow_buffer.py    | 12 +++---
 .../cudf/cudf/core/buffer/spillable_buffer.py | 21 ++-------
 python/cudf/cudf/core/column/categorical.py   | 29 +++++++------
 python/cudf/cudf/core/column/column.py        | 43 ++++++++++---------
 python/cudf/cudf/core/dataframe.py            |  7 +--
 python/cudf/cudf/core/frame.py                | 15 +++----
 python/cudf/cudf/core/indexed_frame.py        | 21 +++++----
 python/cudf/cudf/core/single_column_frame.py  |  4 +-
 python/cudf/cudf/core/tools/datetimes.py      | 14 +++---
 12 files changed, 87 insertions(+), 109 deletions(-)

diff --git a/python/cudf/cudf/_lib/column.pyi b/python/cudf/cudf/_lib/column.pyi
index bd53801a972..93edef311db 100644
--- a/python/cudf/cudf/_lib/column.pyi
+++ b/python/cudf/cudf/_lib/column.pyi
@@ -4,12 +4,12 @@ from __future__ import annotations
 
 from typing import Dict, Optional, Tuple, TypeVar
 
+from typing_extensions import Self
+
 from cudf._typing import Dtype, DtypeObj, ScalarLike
 from cudf.core.buffer import Buffer
 from cudf.core.column import ColumnBase
 
-T = TypeVar("T")
-
 class Column:
     _data: Optional[Buffer]
     _mask: Optional[Buffer]
@@ -56,7 +56,7 @@ class Column:
     @property
     def mask_ptr(self) -> int: ...
     def set_base_mask(self, value: Optional[Buffer]) -> None: ...
-    def set_mask(self: T, value: Optional[Buffer]) -> T: ...
+    def set_mask(self, value: Optional[Buffer]) -> Self: ...
     @property
     def null_count(self) -> int: ...
     @property
@@ -68,7 +68,8 @@ class Column:
     def set_base_children(self, value: Tuple[ColumnBase, ...]) -> None: ...
     def _mimic_inplace(
         self, other_col: ColumnBase, inplace=False
-    ) -> Optional[ColumnBase]: ...
+    ) -> Optional[Self]: ...
+
     # TODO: The val parameter should be Scalar, not ScalarLike
     @staticmethod
     def from_scalar(val: ScalarLike, size: int) -> ColumnBase: ...
diff --git a/python/cudf/cudf/core/_base_index.py b/python/cudf/cudf/core/_base_index.py
index 68c52a8b9e8..a2e3bc44f3a 100644
--- a/python/cudf/cudf/core/_base_index.py
+++ b/python/cudf/cudf/core/_base_index.py
@@ -5,9 +5,10 @@
 import pickle
 import warnings
 from functools import cached_property
-from typing import Any, Set, TypeVar
+from typing import Any, Set
 
 import pandas as pd
+from typing_extensions import Self
 
 import cudf
 from cudf._lib.copying import _gather_map_is_valid, gather
@@ -62,8 +63,6 @@
 Float64Index([1.0, 2.0, 3.0], dtype='float64')
 """
 
-BaseIndexT = TypeVar("BaseIndexT", bound="BaseIndex")
-
 
 class BaseIndex(Serializable):
     """Base class for all cudf Index types."""
@@ -101,8 +100,8 @@ def __contains__(self, item):
         return item in self._values
 
     def _copy_type_metadata(
-        self: BaseIndexT, other: BaseIndexT, *, override_dtypes=None
-    ) -> BaseIndexT:
+        self, other: Self, *, override_dtypes=None
+    ) -> Self:
         raise NotImplementedError
 
     def get_level_values(self, level):
@@ -1451,7 +1450,6 @@ def get_slice_bound(self, label, side, kind=None):
         raise NotImplementedError
 
     def __array_function__(self, func, types, args, kwargs):
-
         # check if the function is implemented for the current type
         cudf_index_module = type(self)
         for submodule in func.__module__.split(".")[1:]:
diff --git a/python/cudf/cudf/core/buffer/buffer.py b/python/cudf/cudf/core/buffer/buffer.py
index abf1ec47e3d..97f3b16bec8 100644
--- a/python/cudf/cudf/core/buffer/buffer.py
+++ b/python/cudf/cudf/core/buffer/buffer.py
@@ -5,9 +5,10 @@
 import math
 import pickle
 from types import SimpleNamespace
-from typing import Any, Dict, Mapping, Optional, Sequence, Tuple, Type, TypeVar
+from typing import Any, Dict, Mapping, Optional, Sequence, Tuple
 
 import numpy
+from typing_extensions import Self
 
 import rmm
 
@@ -15,8 +16,6 @@
 from cudf.core.abc import Serializable
 from cudf.utils.string import format_bytes
 
-T = TypeVar("T", bound="Buffer")
-
 
 def host_memory_allocation(nbytes: int) -> memoryview:
     """Allocate host memory using NumPy
@@ -108,7 +107,7 @@ def __init__(self):
         )
 
     @classmethod
-    def _from_device_memory(cls: Type[T], data: Any) -> T:
+    def _from_device_memory(cls, data: Any) -> Self:
         """Create a Buffer from an object exposing `__cuda_array_interface__`.
 
         No data is being copied.
@@ -139,7 +138,7 @@ def _from_device_memory(cls: Type[T], data: Any) -> T:
         return ret
 
     @classmethod
-    def _from_host_memory(cls: Type[T], data: Any) -> T:
+    def _from_host_memory(cls, data: Any) -> Self:
         """Create a Buffer from a buffer or array like object
 
         Data must implement `__array_interface__`, the buffer protocol, and/or
@@ -310,7 +309,7 @@ def serialize(self) -> Tuple[dict, list]:
         return header, frames
 
     @classmethod
-    def deserialize(cls: Type[T], header: dict, frames: list) -> T:
+    def deserialize(cls, header: dict, frames: list) -> Self:
         """Create an Buffer from a serialized representation.
 
         Parameters
diff --git a/python/cudf/cudf/core/buffer/cow_buffer.py b/python/cudf/cudf/core/buffer/cow_buffer.py
index 16a1e3942e7..6243916b91b 100644
--- a/python/cudf/cudf/core/buffer/cow_buffer.py
+++ b/python/cudf/cudf/core/buffer/cow_buffer.py
@@ -4,15 +4,15 @@
 
 import weakref
 from collections import defaultdict
-from typing import Any, DefaultDict, Tuple, Type, TypeVar
+from typing import Any, DefaultDict, Tuple
 from weakref import WeakSet
 
+from typing_extensions import Self
+
 import rmm
 
 from cudf.core.buffer.buffer import Buffer
 
-T = TypeVar("T", bound="CopyOnWriteBuffer")
-
 
 def _keys_cleanup(ptr):
     weak_set_values = CopyOnWriteBuffer._instances[ptr]
@@ -55,9 +55,7 @@ def _finalize_init(self):
         weakref.finalize(self, _keys_cleanup, self._ptr)
 
     @classmethod
-    def _from_device_memory(
-        cls: Type[T], data: Any, *, exposed: bool = False
-    ) -> T:
+    def _from_device_memory(cls, data: Any, *, exposed: bool = False) -> Self:
         """Create a Buffer from an object exposing `__cuda_array_interface__`.
 
         No data is being copied.
@@ -82,7 +80,7 @@ def _from_device_memory(
         return ret
 
     @classmethod
-    def _from_host_memory(cls: Type[T], data: Any) -> T:
+    def _from_host_memory(cls, data: Any) -> Self:
         ret = super()._from_host_memory(data)
         ret._finalize_init()
         return ret
diff --git a/python/cudf/cudf/core/buffer/spillable_buffer.py b/python/cudf/cudf/core/buffer/spillable_buffer.py
index 169b52b828e..c1bc49c7a9e 100644
--- a/python/cudf/cudf/core/buffer/spillable_buffer.py
+++ b/python/cudf/cudf/core/buffer/spillable_buffer.py
@@ -7,18 +7,10 @@
 import time
 import weakref
 from threading import RLock
-from typing import (
-    TYPE_CHECKING,
-    Any,
-    Dict,
-    List,
-    Optional,
-    Tuple,
-    Type,
-    TypeVar,
-)
+from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple
 
 import numpy
+from typing_extensions import Self
 
 import rmm
 
@@ -34,9 +26,6 @@
     from cudf.core.buffer.spill_manager import SpillManager
 
 
-T = TypeVar("T", bound="SpillableBuffer")
-
-
 def get_spillable_owner(data) -> Optional[SpillableBuffer]:
     """Get the spillable owner of `data`, if any exist
 
@@ -212,9 +201,7 @@ def _finalize_init(self, ptr_desc: Dict[str, Any], exposed: bool) -> None:
         self._manager.add(self)
 
     @classmethod
-    def _from_device_memory(
-        cls: Type[T], data: Any, *, exposed: bool = False
-    ) -> T:
+    def _from_device_memory(cls, data: Any, *, exposed: bool = False) -> Self:
         """Create a spillabe buffer from device memory.
 
         No data is being copied.
@@ -236,7 +223,7 @@ def _from_device_memory(
         return ret
 
     @classmethod
-    def _from_host_memory(cls: Type[T], data: Any) -> T:
+    def _from_host_memory(cls, data: Any) -> Self:
         """Create a spillabe buffer from host memory.
 
         Data must implement `__array_interface__`, the buffer protocol, and/or
diff --git a/python/cudf/cudf/core/column/categorical.py b/python/cudf/cudf/core/column/categorical.py
index c6d7f779884..39332807139 100644
--- a/python/cudf/cudf/core/column/categorical.py
+++ b/python/cudf/cudf/core/column/categorical.py
@@ -11,6 +11,7 @@
 import pandas as pd
 import pyarrow as pa
 from numba import cuda
+from typing_extensions import Self
 
 import cudf
 from cudf import _lib as libcudf
@@ -716,7 +717,6 @@ def __init__(
         null_count: Optional[int] = None,
         children: Tuple["column.ColumnBase", ...] = (),
     ):
-
         if size is None:
             for child in children:
                 assert child.offset == 0
@@ -874,7 +874,7 @@ def _fill(
         begin: int,
         end: int,
         inplace: bool = False,
-    ) -> "column.ColumnBase":
+    ) -> Self:
         if end <= begin or begin >= self.size:
             return self if inplace else self.copy()
 
@@ -890,17 +890,20 @@ def _fill(
 
     def slice(
         self, start: int, stop: int, stride: Optional[int] = None
-    ) -> "column.ColumnBase":
+    ) -> Self:
         codes = self.codes.slice(start, stop, stride)
-        return cudf.core.column.build_categorical_column(
-            categories=self.categories,
-            codes=cudf.core.column.build_column(
-                codes.base_data, dtype=codes.dtype
+        return cast(
+            Self,
+            cudf.core.column.build_categorical_column(
+                categories=self.categories,
+                codes=cudf.core.column.build_column(
+                    codes.base_data, dtype=codes.dtype
+                ),
+                mask=codes.base_mask,
+                ordered=self.ordered,
+                size=codes.size,
+                offset=codes.offset,
             ),
-            mask=codes.base_mask,
-            ordered=self.ordered,
-            size=codes.size,
-            offset=codes.offset,
         )
 
     def _binaryop(self, other: ColumnBinaryOperand, op: str) -> ColumnBase:
@@ -1356,7 +1359,7 @@ def _get_decategorized_column(self) -> ColumnBase:
         out = out.set_mask(self.mask)
         return out
 
-    def copy(self, deep: bool = True) -> CategoricalColumn:
+    def copy(self, deep: bool = True) -> Self:
         result_col = super().copy(deep=deep)
         if deep:
             result_col.categories = libcudf.copying.copy_column(
@@ -1370,7 +1373,7 @@ def memory_usage(self) -> int:
 
     def _mimic_inplace(
         self, other_col: ColumnBase, inplace: bool = False
-    ) -> Optional[ColumnBase]:
+    ) -> Optional[Self]:
         out = super()._mimic_inplace(other_col, inplace=inplace)
         if inplace and isinstance(other_col, CategoricalColumn):
             self._codes = other_col._codes
diff --git a/python/cudf/cudf/core/column/column.py b/python/cudf/cudf/core/column/column.py
index 6557001f884..5ca3cf43e97 100644
--- a/python/cudf/cudf/core/column/column.py
+++ b/python/cudf/cudf/core/column/column.py
@@ -2,6 +2,7 @@
 
 from __future__ import annotations
 
+import builtins
 import pickle
 import warnings
 from functools import cached_property
@@ -25,6 +26,7 @@
 import pandas as pd
 import pyarrow as pa
 from numba import cuda
+from typing_extensions import Self
 
 import rmm
 
@@ -98,9 +100,6 @@
     from pandas.core.arrays._arrow_utils import ArrowIntervalType
 
 T = TypeVar("T", bound="ColumnBase")
-# TODO: This workaround allows type hints for `slice`, since `slice` is a
-# method in ColumnBase.
-Slice = TypeVar("Slice", bound=slice)
 
 
 class ColumnBase(Column, Serializable, BinaryOperand, Reducible):
@@ -246,11 +245,11 @@ def values(self) -> "cupy.ndarray":
         return cupy.asarray(self.data_array_view(mode="write"))
 
     def find_and_replace(
-        self: T,
+        self,
         to_replace: ColumnLike,
         replacement: ColumnLike,
         all_nan: bool = False,
-    ) -> T:
+    ) -> Self:
         raise NotImplementedError
 
     def clip(self, lo: ScalarLike, hi: ScalarLike) -> ColumnBase:
@@ -399,7 +398,7 @@ def _fill(
         begin: int,
         end: int,
         inplace: bool = False,
-    ) -> Optional[ColumnBase]:
+    ) -> Optional[Self]:
         if end <= begin or begin >= self.size:
             return self if inplace else self.copy()
 
@@ -439,15 +438,15 @@ def nullmask(self) -> Buffer:
             raise ValueError("Column has no null mask")
         return self.mask_array_view(mode="read")
 
-    def force_deep_copy(self: T) -> T:
+    def force_deep_copy(self) -> Self:
         """
         A method to create deep copy irrespective of whether
         `copy-on-write` is enabled.
         """
         result = libcudf.copying.copy_column(self)
-        return cast(T, result._with_type_metadata(self.dtype))
+        return result._with_type_metadata(self.dtype)
 
-    def copy(self: T, deep: bool = True) -> T:
+    def copy(self, deep: bool = True) -> Self:
         """
         Makes a copy of the Column.
 
@@ -469,7 +468,7 @@ def copy(self: T, deep: bool = True) -> T:
             return self.force_deep_copy()
         else:
             return cast(
-                T,
+                Self,
                 build_column(
                     data=self.base_data
                     if self.base_data is None
@@ -611,8 +610,10 @@ def _wrap_binop_normalization(self, other):
         return self.normalize_binop_value(other)
 
     def _scatter_by_slice(
-        self, key: Slice, value: Union[cudf.core.scalar.Scalar, ColumnBase]
-    ) -> Optional[ColumnBase]:
+        self,
+        key: builtins.slice,
+        value: Union[cudf.core.scalar.Scalar, ColumnBase],
+    ) -> Optional[Self]:
         """If this function returns None, it's either a no-op (slice is empty),
         or the inplace replacement is already performed (fill-in-place).
         """
@@ -650,7 +651,7 @@ def _scatter_by_column(
         self,
         key: cudf.core.column.NumericalColumn,
         value: Union[cudf.core.scalar.Scalar, ColumnBase],
-    ) -> ColumnBase:
+    ) -> Self:
         if is_bool_dtype(key.dtype):
             # `key` is boolean mask
             if len(key) != len(self):
@@ -701,11 +702,11 @@ def _check_scatter_key_length(
                 raise ValueError(msg)
 
     def fillna(
-        self: T,
+        self,
         value: Any = None,
         method: Optional[str] = None,
         dtype: Optional[Dtype] = None,
-    ) -> T:
+    ) -> Self:
         """Fill null values with ``value``.
 
         Returns a copy with null filled.
@@ -773,8 +774,8 @@ def quantile(
         raise TypeError(f"cannot perform quantile with type {self.dtype}")
 
     def take(
-        self: T, indices: ColumnBase, nullify: bool = False, check_bounds=True
-    ) -> T:
+        self, indices: ColumnBase, nullify: bool = False, check_bounds=True
+    ) -> Self:
         """Return Column by taking values from the corresponding *indices*.
 
         Skip bounds checking if check_bounds is False.
@@ -782,7 +783,7 @@ def take(
         """
         # Handle zero size
         if indices.size == 0:
-            return cast(T, column_empty_like(self, newsize=0))
+            return cast(Self, column_empty_like(self, newsize=0))
 
         # TODO: For performance, the check and conversion of gather map should
         # be done by the caller. This check will be removed in future release.
@@ -1411,8 +1412,10 @@ def column_empty_like(
         and is_categorical_dtype(column.dtype)
         and dtype == column.dtype
     ):
-        column = cast("cudf.core.column.CategoricalColumn", column)
-        codes = column_empty_like(column.codes, masked=masked, newsize=newsize)
+        catcolumn = cast("cudf.core.column.CategoricalColumn", column)
+        codes = column_empty_like(
+            catcolumn.codes, masked=masked, newsize=newsize
+        )
         return build_column(
             data=None,
             dtype=dtype,
diff --git a/python/cudf/cudf/core/dataframe.py b/python/cudf/cudf/core/dataframe.py
index 0fb82b8583c..2aa370ac8e5 100644
--- a/python/cudf/cudf/core/dataframe.py
+++ b/python/cudf/cudf/core/dataframe.py
@@ -22,7 +22,6 @@
     Optional,
     Set,
     Tuple,
-    TypeVar,
     Union,
 )
 
@@ -37,6 +36,7 @@
 from pandas.core.dtypes.common import is_float, is_integer
 from pandas.io.formats import console
 from pandas.io.formats.printing import pprint_thing
+from typing_extensions import Self
 
 import cudf
 import cudf.core.common
@@ -105,9 +105,6 @@
     _external_only_api,
 )
 
-T = TypeVar("T", bound="DataFrame")
-
-
 _cupy_nan_methods_map = {
     "min": "nanmin",
     "max": "nanmax",
@@ -1306,7 +1303,7 @@ def __delitem__(self, name):
         self._drop_column(name)
 
     @_cudf_nvtx_annotate
-    def _slice(self: T, arg: slice) -> T:
+    def _slice(self, arg: slice) -> Self:
         """
         _slice : slice the frame as per the arg
 
diff --git a/python/cudf/cudf/core/frame.py b/python/cudf/cudf/core/frame.py
index 230a5054a00..26b1ee971da 100644
--- a/python/cudf/cudf/core/frame.py
+++ b/python/cudf/cudf/core/frame.py
@@ -16,7 +16,6 @@
     MutableMapping,
     Optional,
     Tuple,
-    TypeVar,
     Union,
 )
 
@@ -24,6 +23,7 @@
 import numpy as np
 import pandas as pd
 import pyarrow as pa
+from typing_extensions import Self
 
 import cudf
 from cudf import _lib as libcudf
@@ -45,8 +45,6 @@
 from cudf.utils.dtypes import find_common_type
 from cudf.utils.utils import _array_ufunc, _cudf_nvtx_annotate
 
-T = TypeVar("T", bound="Frame")
-
 
 # TODO: It looks like Frame is missing a declaration of `copy`, need to add
 class Frame(BinaryOperand, Scannable):
@@ -146,8 +144,8 @@ def _from_columns_like_self(
         return frame._copy_type_metadata(self, override_dtypes=override_dtypes)
 
     def _mimic_inplace(
-        self: T, result: T, inplace: bool = False
-    ) -> Optional[Frame]:
+        self, result: Self, inplace: bool = False
+    ) -> Optional[Self]:
         if inplace:
             for col in self._data:
                 if col in result._data:
@@ -1069,7 +1067,6 @@ def from_arrow(cls, data):
         # Handle dict arrays
         cudf_category_frame = {}
         if len(dict_indices):
-
             dict_indices_table = pa.table(dict_indices)
             data = data.drop(dict_indices_table.column_names)
             indices_columns = libcudf.interop.from_arrow(dict_indices_table)
@@ -1191,11 +1188,11 @@ def _positions_from_column_names(self, column_names):
         ]
 
     def _copy_type_metadata(
-        self: T,
-        other: T,
+        self,
+        other: Self,
         *,
         override_dtypes: Optional[abc.Iterable[Optional[Dtype]]] = None,
-    ) -> T:
+    ) -> Self:
         """
         Copy type metadata from each column of `other` to the corresponding
         column of `self`.
diff --git a/python/cudf/cudf/core/indexed_frame.py b/python/cudf/cudf/core/indexed_frame.py
index 95931af038c..3c4d8d84c34 100644
--- a/python/cudf/cudf/core/indexed_frame.py
+++ b/python/cudf/cudf/core/indexed_frame.py
@@ -27,6 +27,7 @@
 import cupy as cp
 import numpy as np
 import pandas as pd
+from typing_extensions import Self
 
 import cudf
 import cudf._lib as libcudf
@@ -224,8 +225,6 @@ def __init__(self, frame):
 _LocIndexerClass = TypeVar("_LocIndexerClass", bound="_FrameIndexer")
 _IlocIndexerClass = TypeVar("_IlocIndexerClass", bound="_FrameIndexer")
 
-T = TypeVar("T", bound="IndexedFrame")
-
 
 class IndexedFrame(Frame):
     """A frame containing an index.
@@ -357,8 +356,8 @@ def _from_columns_like_self(
         )
 
     def _mimic_inplace(
-        self: T, result: T, inplace: bool = False
-    ) -> Optional[Frame]:
+        self, result: Self, inplace: bool = False
+    ) -> Optional[Self]:
         if inplace:
             self._index = result._index
         return super()._mimic_inplace(result, inplace)
@@ -441,7 +440,7 @@ def _scan(self, op, axis=None, skipna=True):
             results[name] = getattr(result_col, op)()
         return self._from_data(results, self._index)
 
-    def _check_data_index_length_match(self: T) -> None:
+    def _check_data_index_length_match(self) -> None:
         # Validate that the number of rows in the data matches the index if the
         # data is not empty. This is a helper for the constructor.
         if self._data.nrows > 0 and self._data.nrows != len(self._index):
@@ -450,7 +449,7 @@ def _check_data_index_length_match(self: T) -> None:
                 f"match length of index ({len(self._index)})"
             )
 
-    def copy(self: T, deep: bool = True) -> T:
+    def copy(self, deep: bool = True) -> Self:
         """Make a copy of this object's indices and data.
 
         When ``deep=True`` (default), a new object will be created with a
@@ -918,12 +917,12 @@ def clip(self, lower=None, upper=None, inplace=False, axis=1):
         return self._mimic_inplace(output, inplace=inplace)
 
     def _copy_type_metadata(
-        self: T,
-        other: T,
+        self,
+        other: Self,
         include_index: bool = True,
         *,
         override_dtypes: Optional[abc.Iterable[Optional[Dtype]]] = None,
-    ) -> T:
+    ) -> Self:
         """
         Copy type metadata from each column of `other` to the corresponding
         column of `self`.
@@ -2322,12 +2321,12 @@ def _n_largest_or_smallest(self, largest, n, columns, keep):
             raise ValueError('keep must be either "first", "last"')
 
     def _align_to_index(
-        self: T,
+        self,
         index: ColumnLike,
         how: str = "outer",
         sort: bool = True,
         allow_non_unique: bool = False,
-    ) -> T:
+    ) -> Self:
         index = cudf.core.index.as_index(index)
 
         if self.index.equals(index):
diff --git a/python/cudf/cudf/core/single_column_frame.py b/python/cudf/cudf/core/single_column_frame.py
index 037ac9c378e..5f07c57fc80 100644
--- a/python/cudf/cudf/core/single_column_frame.py
+++ b/python/cudf/cudf/core/single_column_frame.py
@@ -4,7 +4,7 @@
 from __future__ import annotations
 
 import warnings
-from typing import Any, Dict, Optional, Tuple, TypeVar, Union
+from typing import Any, Dict, Optional, Tuple, Union
 
 import cupy
 import numpy as np
@@ -20,8 +20,6 @@
 from cudf.core.frame import Frame
 from cudf.utils.utils import NotIterable, _cudf_nvtx_annotate
 
-T = TypeVar("T", bound="Frame")
-
 
 class SingleColumnFrame(Frame, NotIterable):
     """A one-dimensional frame.
diff --git a/python/cudf/cudf/core/tools/datetimes.py b/python/cudf/cudf/core/tools/datetimes.py
index 92ef49e92d9..0ee9f511061 100644
--- a/python/cudf/cudf/core/tools/datetimes.py
+++ b/python/cudf/cudf/core/tools/datetimes.py
@@ -1,15 +1,16 @@
-# Copyright (c) 2019-2022, NVIDIA CORPORATION.
+# Copyright (c) 2019-2023, NVIDIA CORPORATION.
 
 import math
 import re
 import warnings
-from typing import Sequence, Type, TypeVar, Union
+from typing import Sequence, Union
 
 import cupy as cp
 import numpy as np
 import pandas as pd
 import pandas.tseries.offsets as pd_offset
 from pandas.core.tools.datetimes import _unit_map
+from typing_extensions import Self
 
 import cudf
 from cudf import _lib as libcudf
@@ -373,9 +374,6 @@ def get_units(value):
     return value
 
 
-_T = TypeVar("_T", bound="DateOffset")
-
-
 class DateOffset:
     """
     An object used for binary ops where calendrical arithmetic
@@ -647,7 +645,7 @@ def __repr__(self):
         return repr_str
 
     @classmethod
-    def _from_freqstr(cls: Type[_T], freqstr: str) -> _T:
+    def _from_freqstr(cls, freqstr: str) -> Self:
         """
         Parse a string and return a DateOffset object
         expects strings of the form 3D, 25W, 10ms, 42ns, etc.
@@ -669,9 +667,9 @@ def _from_freqstr(cls: Type[_T], freqstr: str) -> _T:
 
     @classmethod
     def _from_pandas_ticks_or_weeks(
-        cls: Type[_T],
+        cls,
         tick: Union[pd.tseries.offsets.Tick, pd.tseries.offsets.Week],
-    ) -> _T:
+    ) -> Self:
         return cls(**{cls._TICK_OR_WEEK_TO_UNITS[type(tick)]: tick.n})
 
     def _maybe_as_fast_pandas_offset(self):

From 1fd7214b3661e1afd0df228486425e2cbe4ea7ce Mon Sep 17 00:00:00 2001
From: Lawrence Mitchell <lmitchell@nvidia.com>
Date: Fri, 12 May 2023 14:30:19 +0100
Subject: [PATCH 2/3] Remove unnecessary type quotes

---
 python/cudf/cudf/core/column/column.py    | 2 +-
 python/cudf/cudf/core/column/interval.py  | 3 +--
 python/cudf/cudf/core/column/numerical.py | 2 +-
 python/cudf/cudf/core/column/string.py    | 2 +-
 python/cudf/cudf/core/column/struct.py    | 2 +-
 5 files changed, 5 insertions(+), 6 deletions(-)

diff --git a/python/cudf/cudf/core/column/column.py b/python/cudf/cudf/core/column/column.py
index 5ca3cf43e97..62920c78f79 100644
--- a/python/cudf/cudf/core/column/column.py
+++ b/python/cudf/cudf/core/column/column.py
@@ -202,7 +202,7 @@ def __repr__(self):
 
     def to_pandas(
         self, index: Optional[pd.Index] = None, **kwargs
-    ) -> "pd.Series":
+    ) -> pd.Series:
         """Convert object to pandas type.
 
         The default implementation falls back to PyArrow for the conversion.
diff --git a/python/cudf/cudf/core/column/interval.py b/python/cudf/cudf/core/column/interval.py
index 1b9caa42ecf..38384d09126 100644
--- a/python/cudf/cudf/core/column/interval.py
+++ b/python/cudf/cudf/core/column/interval.py
@@ -21,7 +21,6 @@ def __init__(
         children=(),
         closed="right",
     ):
-
         super().__init__(
             data=None,
             dtype=dtype,
@@ -128,7 +127,7 @@ def as_interval_column(self, dtype, **kwargs):
 
     def to_pandas(
         self, index: Optional[pd.Index] = None, **kwargs
-    ) -> "pd.Series":
+    ) -> pd.Series:
         # Note: This does not handle null values in the interval column.
         # However, this exact sequence (calling __from_arrow__ on the output of
         # self.to_arrow) is currently the best known way to convert interval
diff --git a/python/cudf/cudf/core/column/numerical.py b/python/cudf/cudf/core/column/numerical.py
index 840858c4bdb..39798320f88 100644
--- a/python/cudf/cudf/core/column/numerical.py
+++ b/python/cudf/cudf/core/column/numerical.py
@@ -723,7 +723,7 @@ def to_pandas(
         index: Optional[pd.Index] = None,
         nullable: bool = False,
         **kwargs,
-    ) -> "pd.Series":
+    ) -> pd.Series:
         if nullable and self.dtype in np_dtypes_to_pandas_dtypes:
             pandas_nullable_dtype = np_dtypes_to_pandas_dtypes[self.dtype]
             arrow_array = self.to_arrow()
diff --git a/python/cudf/cudf/core/column/string.py b/python/cudf/cudf/core/column/string.py
index 8e83d0c72b6..a3163f1cebe 100644
--- a/python/cudf/cudf/core/column/string.py
+++ b/python/cudf/cudf/core/column/string.py
@@ -5632,7 +5632,7 @@ def to_pandas(
         index: Optional[pd.Index] = None,
         nullable: bool = False,
         **kwargs,
-    ) -> "pd.Series":
+    ) -> pd.Series:
         if nullable:
             pandas_array = pd.StringDtype().__from_arrow__(self.to_arrow())
             pd_series = pd.Series(pandas_array, copy=False)
diff --git a/python/cudf/cudf/core/column/struct.py b/python/cudf/cudf/core/column/struct.py
index 6306bd1f32d..8558faa7f24 100644
--- a/python/cudf/cudf/core/column/struct.py
+++ b/python/cudf/cudf/core/column/struct.py
@@ -60,7 +60,7 @@ def to_arrow(self):
 
     def to_pandas(
         self, index: Optional[pd.Index] = None, **kwargs
-    ) -> "pd.Series":
+    ) -> pd.Series:
         # We cannot go via Arrow's `to_pandas` because of the following issue:
         # https://issues.apache.org/jira/browse/ARROW-12680
 

From 9796934ac9a4f8cbce9cf1f860942cf3fcafae32 Mon Sep 17 00:00:00 2001
From: Lawrence Mitchell <lmitchell@nvidia.com>
Date: Fri, 12 May 2023 14:34:48 +0100
Subject: [PATCH 3/3] Remove more TypeVar usage

---
 python/cudf/cudf/core/column/column.py | 3 ---
 python/cudf/cudf/core/index.py         | 5 +----
 2 files changed, 1 insertion(+), 7 deletions(-)

diff --git a/python/cudf/cudf/core/column/column.py b/python/cudf/cudf/core/column/column.py
index 62920c78f79..607bf83ff6c 100644
--- a/python/cudf/cudf/core/column/column.py
+++ b/python/cudf/cudf/core/column/column.py
@@ -16,7 +16,6 @@
     Optional,
     Sequence,
     Tuple,
-    TypeVar,
     Union,
     cast,
 )
@@ -99,8 +98,6 @@
 else:
     from pandas.core.arrays._arrow_utils import ArrowIntervalType
 
-T = TypeVar("T", bound="ColumnBase")
-
 
 class ColumnBase(Column, Serializable, BinaryOperand, Reducible):
     _VALID_REDUCTIONS = {
diff --git a/python/cudf/cudf/core/index.py b/python/cudf/cudf/core/index.py
index 0ec06f8d81f..f5dc8298bd2 100644
--- a/python/cudf/cudf/core/index.py
+++ b/python/cudf/cudf/core/index.py
@@ -15,7 +15,6 @@
     Optional,
     Tuple,
     Type,
-    TypeVar,
     Union,
 )
 
@@ -65,8 +64,6 @@
 )
 from cudf.utils.utils import _cudf_nvtx_annotate, search_range
 
-T = TypeVar("T", bound="Frame")
-
 
 def _lexsorted_equal_range(
     idx: Union[GenericIndex, cudf.MultiIndex],
@@ -1048,7 +1045,7 @@ def _from_data(
 
     def _binaryop(
         self,
-        other: T,
+        other: Frame,
         op: str,
         fill_value: Any = None,
         *args,