pyrefly

Author: cmp0xff

.pre-commit-config.yaml

@@ -8,7 +8,7 @@ repos:
     -   id: ruff-check
         args: [--exit-non-zero-on-fix]
 -   repo: https://github.com/codespell-project/codespell
-    rev: v2.4.2
+    rev: v2.4.3
     hooks:
     - id: codespell
       args: [-L, "THIRDPARTY"]

pandas-stubs/_libs/tslibs/offsets.pyi

@@ -18,6 +18,7 @@ import numpy as np
 from pandas import Timestamp
 
 from pandas._typing import (
+    Frequency,
     ShapeT,
     np_ndarray_object,
 )
@@ -104,6 +105,11 @@ class BaseOffset:
 
 class SingleConstructorOffset(BaseOffset): ...
 
+@overload
+def to_offset(freq: None, is_period: bool = False) -> None: ...
+@overload
+def to_offset(freq: Frequency | timedelta, is_period: bool = False) -> BaseOffset: ...
+
 class Tick(SingleConstructorOffset):
     def __init__(self, n: int = ..., normalize: bool = ...) -> None: ...
     @property

pandas-stubs/core/series.pyi

@@ -128,6 +128,7 @@ from pandas.core.window.rolling import (
     Rolling,
     Window,
 )
+from typing_extensions import override
 import xarray as xr
 
 from pandas._libs.interval import Interval
@@ -1874,7 +1875,8 @@ class Series(IndexOpsMixin[S1], ElementOpsMixin[S1], NDFrame):
     @final
     def last_valid_index(self) -> Scalar: ...
     @overload
-    def value_counts(  # pyrefly: ignore
+    @override
+    def value_counts(
         self,
         normalize: Literal[False] = False,
         sort: _bool = ...,

pandas-stubs/tseries/frequencies.pyi

@@ -1,18 +1,7 @@
-from datetime import timedelta
-from typing import overload
+from pandas.core.indexes.datetimes import DatetimeIndex
+from pandas.core.indexes.timedeltas import TimedeltaIndex
+from pandas.core.series import Series
 
-from pandas import (
-    DatetimeIndex,
-    Series,
-    TimedeltaIndex,
-)
+from pandas._libs.tslibs.offsets import to_offset as to_offset
 
-from pandas._typing import Frequency
-
-from pandas.tseries.offsets import BaseOffset
-
-@overload
-def to_offset(freq: None, is_period: bool = False) -> None: ...
-@overload
-def to_offset(freq: Frequency | timedelta, is_period: bool = False) -> BaseOffset: ...
 def infer_freq(index: Series | DatetimeIndex | TimedeltaIndex) -> str | None: ...

pyproject.toml

@@ -347,10 +347,12 @@ filterwarnings = [
 project-includes = ["pandas-stubs", "tests"]
 enabled-ignores = ["pyrefly"]
 python-version = "3.11"
+min-severity = "warn"
 
 [tool.pyrefly.errors]
 explicit-any = false  # We do use implicit Any
 implicit-any-type-argument = false  # We do use implicit Any
+implicit-bool = false  # We do use implicit bool
 untyped-import = false  # Import discovery
 
 [tool.ty.environment]

tests/__init__.py

@@ -91,8 +91,10 @@ def check(
     value: Any
     if isinstance(actual, pd.Series):
         # cast is by design microsoft/pyright#11191
+        # pyrefly: ignore[redundant-cast]
         value = cast(pd.Series, actual).iloc[index_to_check_for_type]
     elif isinstance(actual, pd.Index):
+        # pyrefly: ignore[redundant-cast]
         # cast is by design microsoft/pyright#11191
         value = cast(pd.Index, actual)[index_to_check_for_type]
     elif isinstance(actual, BaseGroupBy):

tests/frame/test_frame.py

@@ -297,7 +297,10 @@ def test_assign() -> None:
     df = pd.DataFrame({"a": [1, 2, 3], 1: [4, 5, 6]})
 
     my_unnamed_func = (  # pyright: ignore[reportUnknownVariableType]
-        lambda df: df["a"] * 2  # pyright: ignore[reportUnknownLambdaType]
+        lambda df: df[  # pyright: ignore[reportUnknownLambdaType] # pyrefly: ignore[implicit-any-lambda]
+            "a"
+        ]
+        * 2
     )
 
     def my_named_func_1(df: pd.DataFrame) -> pd.Series[str]:
@@ -4572,12 +4575,14 @@ def func_e(x: pd.DataFrame, k: int) -> pd.Series:
         return x.max() - k * x.min()
 
     check(
+        # pyrefly: ignore[implicity-any-lambda]
         assert_type(df.rolling(2).pipe(lambda x: x.min() - x.max()), pd.DataFrame),
         pd.DataFrame,
     )
     check(assert_type(df.rolling(2).pipe(func_r, k=2), pd.DataFrame), pd.DataFrame)
 
     check(
+        # pyrefly: ignore[implicity-any-lambda]
         assert_type(df.expanding().pipe(lambda x: x.min() - x.max()), pd.DataFrame),
         pd.DataFrame,
     )

tests/test_groupby.py

@@ -156,6 +156,7 @@ def df2series(val: DataFrame) -> Series:
         return val.mean()
 
     def df2scalar(val: DataFrame) -> float:
+        # pyrefly: ignore[unnecessary-type-conversion]
         return float(val.mean().mean())
 
     check(assert_type(GB_DF.resample("ME").aggregate(np.sum), DataFrame), DataFrame)
@@ -245,6 +246,7 @@ def h(val: Resampler[DataFrame]) -> Series:
 
     def i(val: Resampler[DataFrame]) -> float:
         assert isinstance(val, Resampler)
+        # pyrefly: ignore[unnecessary-type-conversion]
         return float(val.mean().mean().mean())
 
     check(assert_type(GB_DF.resample("ME").pipe(i), float), float)
@@ -367,6 +369,7 @@ def f(val: Series) -> float:
     # pipe
     def g(val: Resampler[Series]) -> float:
         assert isinstance(val, Resampler)
+        # pyrefly: ignore[unnecessary-type-conversion]
         return float(val.mean().mean())
 
     check(assert_type(GB_S.resample("ME").pipe(g), float), float)
@@ -382,6 +385,7 @@ def s2series(val: Series) -> Series:
         return Series(val)
 
     def s2scalar(val: Series) -> float:
+        # pyrefly: ignore[unnecessary-type-conversion]
         return float(val.mean())
 
     check(assert_type(GB_S.resample("ME").aggregate(np.sum), Series), Series)
@@ -477,6 +481,7 @@ def df2series(val: DataFrame) -> Series:
         return val.mean()
 
     def df2scalar(val: DataFrame) -> float:
+        # pyrefly: ignore[unnecessary-type-conversion]
         return float(val.mean().mean())
 
     check(assert_type(GB_DF.rolling(1).aggregate(np.sum), DataFrame), DataFrame)
@@ -578,6 +583,7 @@ def f(val: Series) -> float:
     check(assert_type(GB_S.rolling(1).aggregate(f), Series), Series)
 
     def s2scalar(val: Series) -> float:
+        # pyrefly: ignore[unnecessary-type-conversion]
         return float(val.mean())
 
     check(assert_type(GB_S.rolling(1).aggregate(s2scalar), Series), Series)
@@ -652,6 +658,7 @@ def df2series(val: DataFrame) -> Series:
         return val.mean()
 
     def df2scalar(val: DataFrame) -> float:
+        # pyrefly: ignore[unnecessary-type-conversion]
         return float(val.mean().mean())
 
     check(assert_type(GB_DF.expanding(1).aggregate(np.sum), DataFrame), DataFrame)
@@ -757,6 +764,7 @@ def f(val: Series) -> float:
     check(assert_type(GB_S.expanding(1).aggregate(f), Series), Series)
 
     def s2scalar(val: Series) -> float:
+        # pyrefly: ignore[unnecessary-type-conversion]
         return float(val.mean())
 
     check(assert_type(GB_S.expanding(1).aggregate(s2scalar), Series), Series)

tests/test_resampler.py

@@ -160,6 +160,7 @@ def h(val: "DatetimeIndexResampler[DataFrame]") -> Series:
 
     def i(val: "DatetimeIndexResampler[DataFrame]") -> float:
         assert isinstance(val, DatetimeIndexResampler)
+        # pyrefly: ignore[unnecessary-type-conversion]
         return float(val.mean().mean().mean())
 
     check(assert_type(DF.resample("ME").pipe(i), float), float)
@@ -304,6 +305,7 @@ def f(val: "DatetimeIndexResampler[Series]") -> Series:
 
     def g(val: "DatetimeIndexResampler[Series]") -> float:
         assert isinstance(val, DatetimeIndexResampler)
+        # pyrefly: ignore[unnecessary-type-conversion]
         return float(val.mean().mean())
 
     check(assert_type(S.resample("ME").pipe(g), float), float)
@@ -327,6 +329,7 @@ def s2series(val: Series) -> Series:
         return Series(val)
 
     def s2scalar(val: Series) -> float:
+        # pyrefly: ignore[unnecessary-type-conversion]
         return float(val.mean())
 
     check(assert_type(S.resample("ME").aggregate(np.sum), Series), Series)
@@ -361,6 +364,7 @@ def df2series(val: DataFrame) -> Series:
         return val.mean()
 
     def df2scalar(val: DataFrame) -> float:
+        # pyrefly: ignore[unnecessary-type-conversion]
         return float(val.mean().mean())
 
     check(assert_type(DF.resample("ME").aggregate(np.sum), DataFrame), DataFrame)

tests/test_typing.py

@@ -42,8 +42,8 @@ def _to_type(t: Any) -> type:
     if isinstance(t, ExtensionDtype):
         return type(t)
     if issubclass(type(t), np.dtype):
-        return t.type  # type: ignore[no-any-return]
-    return t  # type: ignore[no-any-return]
+        return t.type  # type: ignore[no-any-return] # pyrefly: ignore[no-any-return-explicit]
+    return t  # type: ignore[no-any-return] # pyrefly: ignore[no-any-return-explicit]
 
 
 @pytest.mark.parametrize(("dtype_arg", "alias_map"), DTYPE_ARG_ALIAS_MAPS.items())