TYP: annotation of __init__ return type (PEP 484) (pandas/core/arrays) (#46255)

Author: EkaterinaKuzkina

pandas/core/arrays/_arrow_utils.py

@@ -48,7 +48,7 @@ def pyarrow_array_to_numpy_and_mask(arr, dtype: np.dtype):
 
 
 class ArrowPeriodType(pyarrow.ExtensionType):
-    def __init__(self, freq):
+    def __init__(self, freq) -> None:
         # attributes need to be set first before calling
         # super init (as that calls serialize)
         self._freq = freq
@@ -88,7 +88,7 @@ def to_pandas_dtype(self):
 
 
 class ArrowIntervalType(pyarrow.ExtensionType):
-    def __init__(self, subtype, closed):
+    def __init__(self, subtype, closed) -> None:
         # attributes need to be set first before calling
         # super init (as that calls serialize)
         assert closed in VALID_CLOSED

pandas/core/arrays/_mixins.py

@@ -532,7 +532,7 @@ class ArrowExtensionArray(ExtensionArray):
 
     _data: pa.ChunkedArray
 
-    def __init__(self, values: pa.ChunkedArray):
+    def __init__(self, values: pa.ChunkedArray) -> None:
         self._data = values
 
     def __arrow_array__(self, type=None):

pandas/core/arrays/boolean.py

@@ -297,7 +297,9 @@ class BooleanArray(BaseMaskedArray):
     _TRUE_VALUES = {"True", "TRUE", "true", "1", "1.0"}
     _FALSE_VALUES = {"False", "FALSE", "false", "0", "0.0"}
 
-    def __init__(self, values: np.ndarray, mask: np.ndarray, copy: bool = False):
+    def __init__(
+        self, values: np.ndarray, mask: np.ndarray, copy: bool = False
+    ) -> None:
         if not (isinstance(values, np.ndarray) and values.dtype == np.bool_):
             raise TypeError(
                 "values should be boolean numpy array. Use "

pandas/core/arrays/categorical.py

@@ -367,7 +367,7 @@ def __init__(
         dtype: Dtype | None = None,
         fastpath: bool = False,
         copy: bool = True,
-    ):
+    ) -> None:
 
         dtype = CategoricalDtype._from_values_or_dtype(
             values, categories, ordered, dtype
@@ -2704,7 +2704,7 @@ class CategoricalAccessor(PandasDelegate, PandasObject, NoNewAttributesMixin):
     Categories (3, object): ['a', 'b', 'c']
     """
 
-    def __init__(self, data):
+    def __init__(self, data) -> None:
         self._validate(data)
         self._parent = data.values
         self._index = data.index

pandas/core/arrays/datetimelike.py

@@ -169,7 +169,7 @@ class DatetimeLikeArrayMixin(OpsMixin, NDArrayBackedExtensionArray):
     def _can_hold_na(self) -> bool:
         return True
 
-    def __init__(self, data, dtype: Dtype | None = None, freq=None, copy=False):
+    def __init__(self, data, dtype: Dtype | None = None, freq=None, copy=False) -> None:
         raise AbstractMethodError(self)
 
     @property

pandas/core/arrays/datetimes.py

@@ -254,7 +254,9 @@ class DatetimeArray(dtl.TimelikeOps, dtl.DatelikeOps):
     _dtype: np.dtype | DatetimeTZDtype
     _freq = None
 
-    def __init__(self, values, dtype=DT64NS_DTYPE, freq=None, copy: bool = False):
+    def __init__(
+        self, values, dtype=DT64NS_DTYPE, freq=None, copy: bool = False
+    ) -> None:
         values = extract_array(values, extract_numpy=True)
         if isinstance(values, IntegerArray):
             values = values.to_numpy("int64", na_value=iNaT)

pandas/core/arrays/masked.py

@@ -107,7 +107,7 @@ class BaseMaskedArray(OpsMixin, ExtensionArray):
 
     def __init__(
         self, values: np.ndarray, mask: npt.NDArray[np.bool_], copy: bool = False
-    ):
+    ) -> None:
         # values is supposed to already be validated in the subclass
         if not (isinstance(mask, np.ndarray) and mask.dtype == np.bool_):
             raise TypeError(

pandas/core/arrays/numeric.py

@@ -222,7 +222,7 @@ class NumericArray(BaseMaskedArray):
 
     def __init__(
         self, values: np.ndarray, mask: npt.NDArray[np.bool_], copy: bool = False
-    ):
+    ) -> None:
         checker = self._dtype_cls._checker
         if not (isinstance(values, np.ndarray) and checker(values.dtype)):
             descr = (

pandas/core/arrays/numpy_.py

@@ -66,7 +66,7 @@ class PandasArray(
     # ------------------------------------------------------------------------
     # Constructors
 
-    def __init__(self, values: np.ndarray | PandasArray, copy: bool = False):
+    def __init__(self, values: np.ndarray | PandasArray, copy: bool = False) -> None:
         if isinstance(values, type(self)):
             values = values._ndarray
         if not isinstance(values, np.ndarray):

pandas/core/arrays/period.py

@@ -201,7 +201,7 @@ class PeriodArray(dtl.DatelikeOps):
 
     def __init__(
         self, values, dtype: Dtype | None = None, freq=None, copy: bool = False
-    ):
+    ) -> None:
         freq = validate_dtype_freq(dtype, freq)
 
         if freq is not None:

pandas/core/arrays/sparse/accessor.py

@@ -17,7 +17,7 @@
 class BaseAccessor:
     _validation_msg = "Can only use the '.sparse' accessor with Sparse data."
 
-    def __init__(self, data=None):
+    def __init__(self, data=None) -> None:
         self._parent = data
         self._validate(data)
 

pandas/core/arrays/sparse/array.py

@@ -373,7 +373,7 @@ def __init__(
         kind: SparseIndexKind = "integer",
         dtype: Dtype | None = None,
         copy: bool = False,
-    ):
+    ) -> None:
 
         if fill_value is None and isinstance(dtype, SparseDtype):
             fill_value = dtype.fill_value

pandas/core/arrays/sparse/dtype.py

@@ -81,7 +81,7 @@ class SparseDtype(ExtensionDtype):
     # hash(nan) is (sometimes?) 0.
     _metadata = ("_dtype", "_fill_value", "_is_na_fill_value")
 
-    def __init__(self, dtype: Dtype = np.float64, fill_value: Any = None):
+    def __init__(self, dtype: Dtype = np.float64, fill_value: Any = None) -> None:
 
         if isinstance(dtype, type(self)):
             if fill_value is None:

pandas/core/arrays/string_.py

@@ -97,7 +97,7 @@ class StringDtype(ExtensionDtype):
     na_value = libmissing.NA
     _metadata = ("storage",)
 
-    def __init__(self, storage=None):
+    def __init__(self, storage=None) -> None:
         if storage is None:
             storage = get_option("mode.string_storage")
         if storage not in {"python", "pyarrow"}:
@@ -317,7 +317,7 @@ class StringArray(BaseStringArray, PandasArray):
     # undo the PandasArray hack
     _typ = "extension"
 
-    def __init__(self, values, copy=False):
+    def __init__(self, values, copy=False) -> None:
         values = extract_array(values)
 
         super().__init__(values, copy=copy)

pandas/core/arrays/string_arrow.py

@@ -141,7 +141,7 @@ class ArrowStringArray(
     Length: 4, dtype: string
     """
 
-    def __init__(self, values):
+    def __init__(self, values) -> None:
         self._dtype = StringDtype(storage="pyarrow")
         if isinstance(values, pa.Array):
             self._data = pa.chunked_array([values])

pandas/core/arrays/timedeltas.py

@@ -182,7 +182,7 @@ def dtype(self) -> np.dtype:  # type: ignore[override]
 
     def __init__(
         self, values, dtype=TD64NS_DTYPE, freq=lib.no_default, copy: bool = False
-    ):
+    ) -> None:
         values = extract_array(values, extract_numpy=True)
         if isinstance(values, IntegerArray):
             values = values.to_numpy("int64", na_value=tslibs.iNaT)