TYP: type up NDFrame.pipe GroupBy.pipe etc.

pandas/core/common.py

@@ -8,7 +8,18 @@
 import contextlib
 from functools import partial
 import inspect
-from typing import Any, Collection, Iterable, Iterator, List, Union, cast
+from typing import (
+    TYPE_CHECKING,
+    Any,
+    Callable,
+    Collection,
+    Iterable,
+    Iterator,
+    List,
+    Tuple,
+    Union,
+    cast,
+)
 import warnings
 
 import numpy as np
@@ -28,6 +39,9 @@
 from pandas.core.dtypes.inference import iterable_not_string
 from pandas.core.dtypes.missing import isna, isnull, notnull  # noqa
 
+if TYPE_CHECKING:
+    from pandas._typing import T
+
 
 class SettingWithCopyError(ValueError):
     pass
@@ -405,7 +419,9 @@ def random_state(state=None):
         )
 
 
-def pipe(obj, func, *args, **kwargs):
+def pipe(
+    obj, func: Union[Callable[..., T], Tuple[Callable[..., T], str]], *args, **kwargs
+) -> T:
     """
     Apply a function ``func`` to object ``obj`` either by passing obj as the
     first argument to the function or, in the case that the func is a tuple,

pandas/core/generic.py

@@ -120,6 +120,7 @@
 
 if TYPE_CHECKING:
     from pandas._libs.tslibs import BaseOffset
+    from pandas._typing import T
 
     from pandas.core.frame import DataFrame
     from pandas.core.resample import Resampler
@@ -5351,7 +5352,12 @@ def sample(
 
     @final
     @doc(klass=_shared_doc_kwargs["klass"])
-    def pipe(self, func, *args, **kwargs):
+    def pipe(
+        self,
+        func: Union[Callable[..., T], Tuple[Callable[..., T], str]],
+        *args,
+        **kwargs,
+    ) -> T:
         r"""
         Apply func(self, \*args, \*\*kwargs).
 

pandas/core/groupby/groupby.py

@@ -6,6 +6,7 @@ class providing the base-class of operations.
 (defined in pandas.core.groupby.generic)
 expose these user-facing objects to provide specific functionality.
 """
+from __future__ import annotations
 
 from contextlib import contextmanager
 import datetime
@@ -14,6 +15,7 @@ class providing the base-class of operations.
 from textwrap import dedent
 import types
 from typing import (
+    TYPE_CHECKING,
     Callable,
     Dict,
     FrozenSet,
@@ -78,6 +80,10 @@ class providing the base-class of operations.
 from pandas.core.sorting import get_group_index_sorter
 from pandas.core.util.numba_ import NUMBA_FUNC_CACHE
 
+if TYPE_CHECKING:
+    from pandas._typing import T
+
+
 _common_see_also = """
         See Also
         --------
@@ -476,7 +482,7 @@ def f(self):
 
 
 @contextmanager
-def group_selection_context(groupby: "BaseGroupBy") -> Iterator["BaseGroupBy"]:
+def group_selection_context(groupby: BaseGroupBy) -> Iterator[BaseGroupBy]:
     """
     Set / reset the group_selection_context.
     """
@@ -724,8 +730,8 @@ def _set_group_selection(self) -> None:
 
     @final
     def _set_result_index_ordered(
-        self, result: "OutputFrameOrSeries"
-    ) -> "OutputFrameOrSeries":
+        self, result: OutputFrameOrSeries
+    ) -> OutputFrameOrSeries:
         # set the result index on the passed values object and
         # return the new object, xref 8046
 
@@ -790,7 +796,12 @@ def __getattr__(self, attr: str):
         ),
     )
     @Appender(_pipe_template)
-    def pipe(self, func, *args, **kwargs):
+    def pipe(
+        self,
+        func: Union[Callable[..., T], Tuple[Callable[..., T], str]],
+        *args,
+        **kwargs,
+    ) -> T:
         return com.pipe(self, func, *args, **kwargs)
 
     plot = property(GroupByPlot)
@@ -3058,7 +3069,7 @@ def get_groupby(
     by: Optional[_KeysArgType] = None,
     axis: int = 0,
     level=None,
-    grouper: "Optional[ops.BaseGrouper]" = None,
+    grouper: Optional[ops.BaseGrouper] = None,
     exclusions=None,
     selection=None,
     as_index: bool = True,

pandas/core/resample.py

@@ -1,7 +1,7 @@
 import copy
 from datetime import timedelta
 from textwrap import dedent
-from typing import Dict, Optional, Union, no_type_check
+from typing import TYPE_CHECKING, Callable, Dict, Optional, Tuple, Union, no_type_check
 
 import numpy as np
 
@@ -43,6 +43,9 @@
 from pandas.tseries.frequencies import is_subperiod, is_superperiod
 from pandas.tseries.offsets import DateOffset, Day, Nano, Tick
 
+if TYPE_CHECKING:
+    from pandas._typing import T
+
 _shared_docs_kwargs: Dict[str, str] = {}
 
 
@@ -231,7 +234,12 @@ def _assure_grouper(self):
     2012-08-04  1""",
     )
     @Appender(_pipe_template)
-    def pipe(self, func, *args, **kwargs):
+    def pipe(
+        self,
+        func: Union[Callable[..., T], Tuple[Callable[..., T], str]],
+        *args,
+        **kwargs,
+    ) -> T:
         return super().pipe(func, *args, **kwargs)
 
     _agg_see_also_doc = dedent(