Type annotations for pipe (#55)

* Add type annotations for pipe()

* add annotations in other places as well

* fix formatting of import statement

* update

* format test

Co-authored-by: Nanne Aben <[email protected]>

Author: nanne-aben

setup.py

@@ -21,7 +21,7 @@ def list_packages(source_path: str = src_path) -> None:
 setup(
     name="pandas-stubs",
     package_dir={"": src_path},
-    version="1.1.0.11",
+    version="1.1.0.12",
     description="Type annotations for Pandas",
     long_description=(open("README.md").read()
                       if os.path.exists("README.md") else ""),

tests/snippets/test_frame.py

@@ -500,3 +500,21 @@ def test_types_from_dict() -> None:
     pd.DataFrame.from_dict({'a': {'row1': 2}, 'b': {'row2': 4, 'row1': 4}})
     pd.DataFrame.from_dict({'a': (1, 2, 3), 'b': (2, 4, 5)})
     pd.DataFrame.from_dict(data={'col_1': {'a': 1}, 'col_2': {'a': 1, 'b': 2}}, orient="columns")
+
+
+def test_pipe() -> None:
+    def foo(df: pd.DataFrame) -> pd.DataFrame:
+        return df
+
+    df1: pd.DataFrame = pd.DataFrame({'a': [1]}).pipe(foo)
+
+    df2: pd.DataFrame = (
+        pd.DataFrame({'price': [10, 11, 9, 13, 14, 18, 17, 19], 'volume': [50, 60, 40, 100, 50, 100, 40, 50]})
+        .assign(week_starting=pd.date_range('01/01/2018', periods=8, freq='W'))
+        .resample('M', on='week_starting')
+        .pipe(foo)
+    )
+
+    df3: pd.DataFrame = pd.DataFrame({'a': [1], 'b': [1]}).groupby('a').pipe(foo)
+
+    df4: pd.DataFrame = pd.DataFrame({'a': [1], 'b': [1]}).style.pipe(foo)

third_party/3/pandas/core/common.pyi

@@ -1,6 +1,6 @@
 from pandas._typing import T as T
 
-from typing import Any, Collection, Iterable, Optional, Union
+from typing import Any, Collection, Iterable, Optional, Union, Callable, Tuple, TypeVar, overload
 
 class SettingWithCopyError(ValueError): ...
 class SettingWithCopyWarning(Warning): ...
@@ -33,5 +33,10 @@ def apply_if_callable(maybe_callable: Any, obj: Any, **kwargs: Any) -> Any: ...
 def dict_compat(d: Any) -> Any: ...
 def standardize_mapping(into: Any) -> Any: ...
 def random_state(state: Optional[Any] = ...) -> Any: ...
-def pipe(obj: Any, func: Any, *args: Any, **kwargs: Any) -> Any: ...
 def get_rename_function(mapper: Any) -> Any: ...
+
+PipeReturn = TypeVar("PipeReturn")
+@overload
+def pipe(obj: Any, func: Union[Callable[..., PipeReturn], Tuple[Callable[..., PipeReturn], str]], *args: Any, **kwargs: Any) -> PipeReturn: ...
+@overload
+def pipe(obj: Any, func: PipeReturn, *args: Any, **kwargs: Any) -> PipeReturn: ...

third_party/3/pandas/core/generic.pyi

@@ -2,6 +2,7 @@ from __future__ import annotations
 
 import sys
 from typing import Any, Callable, Dict, Hashable, List, Mapping, Optional, Sequence, Tuple, TypeVar, Union, AnyStr, overload
+from pandas.core.resample import Resampler
 
 if sys.version_info >= (3, 8):
     from typing import Literal
@@ -24,6 +25,7 @@ from pandas.core.internals import BlockManager
 bool_t = bool
 
 Self = TypeVar('Self', bound=NDFrame)
+PipeReturn = TypeVar('PipeReturn')
 
 class NDFrame(PandasObject, SelectionMixin, indexing.IndexingMixin):
     __array_priority__: int = ...
@@ -110,7 +112,10 @@ class NDFrame(PandasObject, SelectionMixin, indexing.IndexingMixin):
     def head(self, n: int = ...) -> FrameOrSeries: ...
     def tail(self, n: int = ...) -> FrameOrSeries: ...
     def sample(self, n: int = ..., frac: float = ..., replace: bool_t = ..., weights: Union[str, ArrayLike] = ..., random_state: Union[int, np.random.RandomState] = ..., axis: Optional[AxisOption] = ...) -> FrameOrSeries: ...
-    def pipe(self, func: Any, *args: Any, **kwargs: Any) -> Any: ...
+    @overload
+    def pipe(self: Any, func: Union[Callable[..., PipeReturn], Tuple[Callable[..., PipeReturn], str]], *args: Any, **kwargs: Any) -> PipeReturn: ...
+    @overload
+    def pipe(self: Any, func: PipeReturn, *args: Any, **kwargs: Any) -> PipeReturn: ...
     def __finalize__(self, other: Any, method: Any = ..., **kwargs: Any) -> FrameOrSeries: ...
     @property
     def values(self) -> np.ndarray: ...
@@ -140,7 +145,7 @@ class NDFrame(PandasObject, SelectionMixin, indexing.IndexingMixin):
     def asfreq(self, freq: Any, method: Any = ..., how: Optional[str]=..., normalize: bool_t=..., fill_value: Any = ...) -> FrameOrSeries: ...
     def at_time(self, time: Any, asof: bool_t=..., axis: Any = ...) -> FrameOrSeries: ...
     def between_time(self, start_time: Any, end_time: Any, include_start: bool_t=..., include_end: bool_t=..., axis: Any = ...) -> FrameOrSeries: ...
-    def resample(self, rule: Any, axis: Any = ..., closed: Optional[str]=..., label: Optional[str]=..., convention: str=..., kind: Optional[str]=..., loffset: Any = ..., base: int=..., on: Any = ..., level: Any = ..., origin: Union[Timestamp, str] = ..., offset: Union[Timedelta, str] = ...) -> Any: ...
+    def resample(self, rule: Any, axis: Any = ..., closed: Optional[str]=..., label: Optional[str]=..., convention: str=..., kind: Optional[str]=..., loffset: Any = ..., base: int=..., on: Any = ..., level: Any = ..., origin: Union[Timestamp, str] = ..., offset: Union[Timedelta, str] = ...) -> Resampler: ...
     def first(self, offset: Any) -> FrameOrSeries: ...
     def last(self, offset: Any) -> FrameOrSeries: ...
     def rank(self, axis: Any = ..., method: str=..., numeric_only: Optional[bool_t]=..., na_option: str=..., ascending: bool_t=..., pct: bool_t=...) -> FrameOrSeries: ...

third_party/3/pandas/core/groupby/groupby.pyi

@@ -15,7 +15,9 @@ from pandas.core.series import Series as Series
 from pandas.core.sorting import get_group_index_sorter as get_group_index_sorter
 from pandas.errors import AbstractMethodError as AbstractMethodError
 from pandas.util._decorators import Appender as Appender, Substitution as Substitution, cache_readonly as cache_readonly
-from typing import Any, List, Optional, Union, Hashable, Callable, Mapping
+from typing import Any, List, Optional, Union, Hashable, Callable, Mapping, TypeVar, Tuple, overload
+
+PipeReturn = TypeVar('PipeReturn')
 
 
 class GroupByPlot(PandasObject):
@@ -53,7 +55,10 @@ class _GroupBy(PandasObject, SelectionMixin):
     @property
     def indices(self) -> Any: ...
     def __getattr__(self, attr: str) -> Any: ...
-    def pipe(self, func: Any, *args: Any, **kwargs: Any) -> Any: ...
+    @overload
+    def pipe(self: Any, func: Union[Callable[..., PipeReturn], Tuple[Callable[..., PipeReturn], str]], *args: Any, **kwargs: Any) -> PipeReturn: ...
+    @overload
+    def pipe(self: Any, func: PipeReturn, *args: Any, **kwargs: Any) -> PipeReturn: ...
     plot: Any = ...
     def get_group(self, name: Any, obj: Optional[Any] = ...) -> Any: ...
     def __iter__(self) -> Any: ...

third_party/3/pandas/core/resample.pyi

@@ -5,7 +5,9 @@ from pandas.core.groupby.grouper import Grouper as Grouper
 from pandas.core.indexes.datetimes import DatetimeIndex as DatetimeIndex
 from pandas.core.indexes.period import PeriodIndex as PeriodIndex
 from pandas.core.indexes.timedeltas import TimedeltaIndex as TimedeltaIndex
-from typing import Any, Optional
+from typing import Any, Optional, TypeVar, Union, Callable, Tuple, overload
+
+PipeReturn = TypeVar('PipeReturn')
 
 class Resampler(_GroupBy, ShallowMixin):
     groupby: Any = ...
@@ -26,7 +28,10 @@ class Resampler(_GroupBy, ShallowMixin):
     def obj(self) -> Any: ...
     @property
     def ax(self) -> Any: ...
-    def pipe(self, func: Any, *args: Any, **kwargs: Any) -> Any: ...
+    @overload
+    def pipe(self: Any, func: Union[Callable[..., PipeReturn], Tuple[Callable[..., PipeReturn], str]], *args: Any, **kwargs: Any) -> PipeReturn: ...
+    @overload
+    def pipe(self: Any, func: PipeReturn, *args: Any, **kwargs: Any) -> PipeReturn: ...
     def aggregate(self, func: Any, *args: Any, **kwargs: Any) -> Any: ...
     agg: Any = ...
     apply: Any = ...

third_party/3/pandas/io/formats/style.pyi

@@ -1,10 +1,11 @@
 from pandas._config import get_option as get_option
 from pandas.util._decorators import Appender as Appender
-from typing import Any, Optional
+from typing import Any, Optional, Callable, TypeVar, Tuple, Union, overload
 
 jinja2: Any
 has_mpl: bool
 no_mpl_message: str
+PipeReturn = TypeVar('PipeReturn')
 
 class Styler:
     loader: Any = ...
@@ -51,4 +52,7 @@ class Styler:
     def highlight_min(self, subset: Optional[Any] = ..., color: str = ..., axis: int = ...) -> Any: ...
     @classmethod
     def from_custom_template(cls, searchpath: Any, name: Any) -> Any: ...
-    def pipe(self, func: Any, *args: Any, **kwargs: Any) -> Any: ...
+    @overload
+    def pipe(self: Any, func: Union[Callable[..., PipeReturn], Tuple[Callable[..., PipeReturn], str]], *args: Any, **kwargs: Any) -> PipeReturn: ...
+    @overload
+    def pipe(self: Any, func: PipeReturn, *args: Any, **kwargs: Any) -> PipeReturn: ...