pyrefly

Author: cmp0xff

pyproject.toml

@@ -339,10 +339,12 @@ 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 implicity bool
 untyped-import = false  # Import discovery
 unused-call-result = false  # results of check(...) are never used
 # TODO: remove when facebook/pyrefly#4427 is resolved

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/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

@@ -158,6 +158,7 @@ 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)
@@ -299,6 +300,7 @@ 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)
@@ -322,6 +324,7 @@ 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)
@@ -356,6 +359,7 @@ 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)