PrettyDict

Author: cmp0xff

pandas-stubs/core/arrays/datetimelike.pyi

@@ -25,7 +25,6 @@ from pandas._typing import (
     TimeNonexistent,
     TimeUnit,
     np_1darray,
-    np_1darray_int64,
 )
 
 DTScalarOrNaT: TypeAlias = DatetimeLikeScalar | NaTType
@@ -65,8 +64,6 @@ class DatetimeLikeArrayMixin(ExtensionOpsMixin, ExtensionArray):
     def ravel(self, *args: Any, **kwargs: Any): ...
     def __iter__(self): ...
     @property
-    def asi8(self) -> np_1darray_int64: ...
-    @property
     def nbytes(self): ...
     def __array__(
         self, dtype: NpDtype | None = None, copy: bool | None = None

pandas-stubs/core/construction.pyi

@@ -1,38 +1,18 @@
 from collections.abc import Sequence
-from datetime import (
-    datetime,
-    timedelta,
-)
 from typing import overload
 
 import numpy as np
 from pandas.core.arrays.base import ExtensionArray
-from pandas.core.arrays.datetimes import DatetimeArray
 from pandas.core.arrays.integer import IntegerArray
-from pandas.core.arrays.timedeltas import TimedeltaArray
 
 from pandas._libs.missing import NAType
 from pandas._typing import (
     IntDtypeArg,
-    TimedeltaDtypeArg,
-    TimestampDtypeArg,
     UIntDtypeArg,
 )
 
 from pandas.core.dtypes.dtypes import ExtensionDtype
 
-@overload
-def array(  # type: ignore[overload-overlap] # pyright: ignore[reportOverlappingOverload]
-    data: Sequence[timedelta | NAType],
-    dtype: TimedeltaDtypeArg | None = None,
-    copy: bool = True,
-) -> TimedeltaArray: ...
-@overload
-def array(  # type: ignore[overload-overlap]
-    data: Sequence[datetime | NAType],
-    dtype: TimestampDtypeArg | None = None,
-    copy: bool = True,
-) -> DatetimeArray: ...
 @overload
 def array(
     data: Sequence[int | NAType],

pandas-stubs/core/indexes/base.pyi

@@ -107,8 +107,6 @@ from pandas._typing import (
     type_t,
 )
 
-from pandas.io.formats.printing import PrettyDict
-
 class InvalidIndexError(Exception): ...
 
 class Index(IndexOpsMixin[S1], ElementOpsMixin[S1]):
@@ -523,8 +521,6 @@ class Index(IndexOpsMixin[S1], ElementOpsMixin[S1]):
     def get_indexer_non_unique(self, target): ...
     @final
     def get_indexer_for(self, target, **kwargs: Any): ...
-    @final
-    def groupby(self, values) -> PrettyDict[Hashable, Self]: ...
     def map(self, mapper, na_action=...) -> Index: ...
     def isin(self, values, level=...) -> np_1darray[np.bool]: ...
     def slice_indexer(