CI: update autotyping

.pre-commit-config.yaml

@@ -413,8 +413,8 @@ repos:
         language: python
         stages: [manual]
         additional_dependencies:
-        - autotyping==22.9.0
-        - libcst==0.4.7
+        - autotyping==23.3.0
+        - libcst==0.4.9
     -   id: check-test-naming
         name: check that test names start with 'test'
         entry: python -m scripts.check_test_naming

pandas/_config/config.py

@@ -737,7 +737,7 @@ def pp(name: str, ks: Iterable[str]) -> list[str]:
 
 
 @contextmanager
-def config_prefix(prefix) -> Generator[None, None, None]:
+def config_prefix(prefix: str) -> Generator[None, None, None]:
     """
     contextmanager for multiple invocations of API with a common prefix
 

pandas/_testing/_random.py

@@ -10,7 +10,9 @@
 RANDS_CHARS = np.array(list(string.ascii_letters + string.digits), dtype=(np.str_, 1))
 
 
-def rands_array(nchars, size, dtype: NpDtype = "O", replace: bool = True) -> np.ndarray:
+def rands_array(
+    nchars, size: int, dtype: NpDtype = "O", replace: bool = True
+) -> np.ndarray:
     """
     Generate an array of byte strings.
     """

pandas/_testing/contexts.py

@@ -154,7 +154,7 @@ def ensure_safe_environment_variables() -> Generator[None, None, None]:
 
 
 @contextmanager
-def with_csv_dialect(name, **kwargs) -> Generator[None, None, None]:
+def with_csv_dialect(name: str, **kwargs) -> Generator[None, None, None]:
     """
     Context manager to temporarily register a CSV dialect for parsing CSV.
 

pandas/compat/numpy/function.py

@@ -342,7 +342,7 @@ def validate_take_with_convert(convert: ndarray | bool | None, args, kwargs) ->
 )
 
 
-def validate_groupby_func(name, args, kwargs, allowed=None) -> None:
+def validate_groupby_func(name: str, args, kwargs, allowed=None) -> None:
     """
     'args' and 'kwargs' should be empty, except for allowed kwargs because all
     of their necessary parameters are explicitly listed in the function

pandas/core/accessor.py

@@ -51,13 +51,13 @@ class PandasDelegate:
     Abstract base class for delegating methods/properties.
     """
 
-    def _delegate_property_get(self, name, *args, **kwargs):
+    def _delegate_property_get(self, name: str, *args, **kwargs):
         raise TypeError(f"You cannot access the property {name}")
 
-    def _delegate_property_set(self, name, value, *args, **kwargs):
+    def _delegate_property_set(self, name: str, value, *args, **kwargs):
         raise TypeError(f"The property {name} cannot be set")
 
-    def _delegate_method(self, name, *args, **kwargs):
+    def _delegate_method(self, name: str, *args, **kwargs):
         raise TypeError(f"You cannot call method {name}")
 
     @classmethod
@@ -91,7 +91,7 @@ def _add_delegate_accessors(
             False skips the missing accessor.
         """
 
-        def _create_delegator_property(name):
+        def _create_delegator_property(name: str):
             def _getter(self):
                 return self._delegate_property_get(name)
 
@@ -107,7 +107,7 @@ def _setter(self, new_values):
                 doc=getattr(delegate, accessor_mapping(name)).__doc__,
             )
 
-        def _create_delegator_method(name):
+        def _create_delegator_method(name: str):
             def f(self, *args, **kwargs):
                 return self._delegate_method(name, *args, **kwargs)
 
@@ -231,7 +231,7 @@ def __get__(self, obj, cls):
 
 
 @doc(klass="", others="")
-def _register_accessor(name, cls):
+def _register_accessor(name: str, cls):
     """
     Register a custom accessor on {klass} objects.
 
@@ -320,21 +320,21 @@ def decorator(accessor):
 
 
 @doc(_register_accessor, klass="DataFrame")
-def register_dataframe_accessor(name):
+def register_dataframe_accessor(name: str):
     from pandas import DataFrame
 
     return _register_accessor(name, DataFrame)
 
 
 @doc(_register_accessor, klass="Series")
-def register_series_accessor(name):
+def register_series_accessor(name: str):
     from pandas import Series
 
     return _register_accessor(name, Series)
 
 
 @doc(_register_accessor, klass="Index")
-def register_index_accessor(name):
+def register_index_accessor(name: str):
     from pandas import Index
 
     return _register_accessor(name, Index)

pandas/core/arrays/_mixins.py

@@ -291,14 +291,14 @@ def __getitem__(
         return result
 
     def _fill_mask_inplace(
-        self, method: str, limit, mask: npt.NDArray[np.bool_]
+        self, method: str, limit: int | None, mask: npt.NDArray[np.bool_]
     ) -> None:
         # (for now) when self.ndim == 2, we assume axis=0
         func = missing.get_fill_func(method, ndim=self.ndim)
         func(self._ndarray.T, limit=limit, mask=mask.T)
 
     @doc(ExtensionArray.fillna)
-    def fillna(self, value=None, method=None, limit=None) -> Self:
+    def fillna(self, value=None, method=None, limit: int | None = None) -> Self:
         value, method = validate_fillna_kwargs(
             value, method, validate_scalar_dict_value=False
         )

pandas/core/arrays/arrow/array.py

@@ -1952,7 +1952,7 @@ def _str_translate(self, table):
             "str.translate not supported with pd.ArrowDtype(pa.string())."
         )
 
-    def _str_wrap(self, width, **kwargs):
+    def _str_wrap(self, width: int, **kwargs):
         raise NotImplementedError(
             "str.wrap not supported with pd.ArrowDtype(pa.string())."
         )

pandas/core/arrays/base.py

@@ -1570,7 +1570,7 @@ def _where(self, mask: npt.NDArray[np.bool_], value) -> Self:
         return result
 
     def _fill_mask_inplace(
-        self, method: str, limit, mask: npt.NDArray[np.bool_]
+        self, method: str, limit: int | None, mask: npt.NDArray[np.bool_]
     ) -> None:
         """
         Replace values in locations specified by 'mask' using pad or backfill.

pandas/core/arrays/categorical.py

@@ -2500,10 +2500,14 @@ def _validate(data):
         if not is_categorical_dtype(data.dtype):
             raise AttributeError("Can only use .cat accessor with a 'category' dtype")
 
-    def _delegate_property_get(self, name):
+    # error: Signature of "_delegate_property_get" incompatible with supertype
+    # "PandasDelegate"
+    def _delegate_property_get(self, name: str):  # type: ignore[override]
         return getattr(self._parent, name)
 
-    def _delegate_property_set(self, name, new_values):
+    # error: Signature of "_delegate_property_set" incompatible with supertype
+    # "PandasDelegate"
+    def _delegate_property_set(self, name: str, new_values):  # type: ignore[override]
         return setattr(self._parent, name, new_values)
 
     @property
@@ -2515,7 +2519,7 @@ def codes(self) -> Series:
 
         return Series(self._parent.codes, index=self._index)
 
-    def _delegate_method(self, name, *args, **kwargs):
+    def _delegate_method(self, name: str, *args, **kwargs):
         from pandas import Series
 
         method = getattr(self._parent, name)

pandas/core/arrays/datetimes.py

@@ -113,7 +113,7 @@ def tz_to_dtype(tz: tzinfo | None, unit: str = "ns"):
         return DatetimeTZDtype(tz=tz, unit=unit)
 
 
-def _field_accessor(name: str, field: str, docstring=None):
+def _field_accessor(name: str, field: str, docstring: str | None = None):
     def f(self):
         values = self._local_timestamps()
 

pandas/core/arrays/interval.py

@@ -889,7 +889,7 @@ def max(self, *, axis: AxisInt | None = None, skipna: bool = True) -> IntervalOr
         indexer = obj.argsort()[-1]
         return obj[indexer]
 
-    def fillna(self, value=None, method=None, limit=None) -> Self:
+    def fillna(self, value=None, method=None, limit: int | None = None) -> Self:
         """
         Fill NA/NaN values using the specified method.
 

pandas/core/arrays/masked.py

@@ -162,7 +162,7 @@ def __getitem__(self, item: PositionalIndexer) -> Self | Any:
 
     @doc(ExtensionArray.fillna)
     @doc(ExtensionArray.fillna)
-    def fillna(self, value=None, method=None, limit=None) -> Self:
+    def fillna(self, value=None, method=None, limit: int | None = None) -> Self:
         value, method = validate_fillna_kwargs(value, method)
 
         mask = self._mask

pandas/core/arrays/period.py

@@ -98,7 +98,7 @@
 }
 
 
-def _field_accessor(name: str, docstring=None):
+def _field_accessor(name: str, docstring: str | None = None):
     def f(self):
         base = self.freq._period_dtype_code
         result = get_period_field_arr(name, self.asi8, base)
@@ -658,7 +658,7 @@ def searchsorted(
         m8arr = self._ndarray.view("M8[ns]")
         return m8arr.searchsorted(npvalue, side=side, sorter=sorter)
 
-    def fillna(self, value=None, method=None, limit=None) -> PeriodArray:
+    def fillna(self, value=None, method=None, limit: int | None = None) -> PeriodArray:
         if method is not None:
             # view as dt64 so we get treated as timelike in core.missing,
             #  similar to dtl._period_dispatch

pandas/core/arrays/sparse/accessor.py

@@ -46,10 +46,10 @@ def _validate(self, data):
         if not isinstance(data.dtype, SparseDtype):
             raise AttributeError(self._validation_msg)
 
-    def _delegate_property_get(self, name, *args, **kwargs):
+    def _delegate_property_get(self, name: str, *args, **kwargs):
         return getattr(self._parent.array, name)
 
-    def _delegate_method(self, name, *args, **kwargs):
+    def _delegate_method(self, name: str, *args, **kwargs):
         if name == "from_coo":
             return self.from_coo(*args, **kwargs)
         elif name == "to_coo":

pandas/core/frame.py

@@ -4936,7 +4936,9 @@ def _series(self):
     # ----------------------------------------------------------------------
     # Reindexing and alignment
 
-    def _reindex_axes(self, axes, level, limit, tolerance, method, fill_value, copy):
+    def _reindex_axes(
+        self, axes, level, limit: int | None, tolerance, method, fill_value, copy
+    ):
         frame = self
 
         columns = axes["columns"]
@@ -4960,7 +4962,7 @@ def _reindex_index(
         copy: bool,
         level: Level,
         fill_value=np.nan,
-        limit=None,
+        limit: int | None = None,
         tolerance=None,
     ):
         new_index, indexer = self.index.reindex(
@@ -4980,7 +4982,7 @@ def _reindex_columns(
         copy: bool,
         level: Level,
         fill_value=None,
-        limit=None,
+        limit: int | None = None,
         tolerance=None,
     ):
         new_columns, indexer = self.columns.reindex(

pandas/core/generic.py

@@ -255,7 +255,7 @@ class NDFrame(PandasObject, indexing.IndexingMixin):
     _accessors: set[str] = set()
     _hidden_attrs: frozenset[str] = frozenset([])
     _metadata: list[str] = []
-    _is_copy: weakref.ReferenceType[NDFrame] | None = None
+    _is_copy: weakref.ReferenceType[NDFrame] | str | None = None
     _mgr: Manager
     _attrs: dict[Hashable, Any]
     _typ: str
@@ -4306,7 +4306,7 @@ def __delitem__(self, key) -> None:
     # Unsorted
 
     @final
-    def _check_inplace_and_allows_duplicate_labels(self, inplace):
+    def _check_inplace_and_allows_duplicate_labels(self, inplace: bool_t):
         if inplace and not self.flags.allows_duplicate_labels:
             raise ValueError(
                 "Cannot specify 'inplace=True' when "
@@ -4384,7 +4384,7 @@ def reindex_like(
         other,
         method: Literal["backfill", "bfill", "pad", "ffill", "nearest"] | None = None,
         copy: bool_t | None = None,
-        limit=None,
+        limit: int | None = None,
         tolerance=None,
     ) -> Self:
         """
@@ -9628,7 +9628,7 @@ def _align_frame(
         copy: bool_t | None = None,
         fill_value=None,
         method=None,
-        limit=None,
+        limit: int | None = None,
         fill_axis: Axis = 0,
     ) -> tuple[Self, DataFrame, Index | None]:
         # defaults
@@ -9684,7 +9684,7 @@ def _align_series(
         copy: bool_t | None = None,
         fill_value=None,
         method=None,
-        limit=None,
+        limit: int | None = None,
         fill_axis: Axis = 0,
     ) -> tuple[Self, Series, Index | None]:
         is_series = isinstance(self, ABCSeries)
@@ -10983,7 +10983,7 @@ def pct_change(
         self,
         periods: int = 1,
         fill_method: Literal["backfill", "bfill", "pad", "ffill"] | None = "pad",
-        limit=None,
+        limit: int | None = None,
         freq=None,
         **kwargs,
     ) -> Self:

pandas/core/groupby/generic.py

@@ -2249,7 +2249,7 @@ def fillna(
         method: FillnaOptions | None = None,
         axis: Axis | None | lib.NoDefault = lib.no_default,
         inplace: bool = False,
-        limit=None,
+        limit: int | None = None,
         downcast=None,
     ) -> DataFrame | None:
         """

pandas/core/groupby/groupby.py

@@ -2781,7 +2781,7 @@ def ewm(self, *args, **kwargs) -> ExponentialMovingWindowGroupby:
         )
 
     @final
-    def _fill(self, direction: Literal["ffill", "bfill"], limit=None):
+    def _fill(self, direction: Literal["ffill", "bfill"], limit: int | None = None):
         """
         Shared function for `pad` and `backfill` to call Cython method.
 
@@ -2868,7 +2868,7 @@ def blk_func(values: ArrayLike) -> ArrayLike:
 
     @final
     @Substitution(name="groupby")
-    def ffill(self, limit=None):
+    def ffill(self, limit: int | None = None):
         """
         Forward fill the values.
 
@@ -2893,7 +2893,7 @@ def ffill(self, limit=None):
 
     @final
     @Substitution(name="groupby")
-    def bfill(self, limit=None):
+    def bfill(self, limit: int | None = None):
         """
         Backward fill the values.
 
@@ -3789,7 +3789,7 @@ def pct_change(
         self,
         periods: int = 1,
         fill_method: FillnaOptions = "ffill",
-        limit=None,
+        limit: int | None = None,
         freq=None,
         axis: Axis | lib.NoDefault = lib.no_default,
     ):

pandas/core/indexes/accessors.py

@@ -81,7 +81,9 @@ def _get_values(self):
             f"cannot convert an object of type {type(data)} to a datetimelike index"
         )
 
-    def _delegate_property_get(self, name):
+    # error: Signature of "_delegate_property_get" incompatible with supertype
+    # "PandasDelegate"
+    def _delegate_property_get(self, name: str):  # type: ignore[override]
         from pandas import Series
 
         values = self._get_values()
@@ -113,13 +115,13 @@ def _delegate_property_get(self, name):
 
         return result
 
-    def _delegate_property_set(self, name, value, *args, **kwargs):
+    def _delegate_property_set(self, name: str, value, *args, **kwargs):
         raise ValueError(
             "modifications to a property of a datetimelike object are not supported. "
             "Change values on the original."
         )
 
-    def _delegate_method(self, name, *args, **kwargs):
+    def _delegate_method(self, name: str, *args, **kwargs):
         from pandas import Series
 
         values = self._get_values()