TYP: __array__

pandas/core/arrays/categorical.py

@@ -1264,7 +1264,7 @@ def shift(self, periods, fill_value=None):
 
         return self.from_codes(codes, dtype=self.dtype)
 
-    def __array__(self, dtype=None):
+    def __array__(self, dtype=None) -> np.ndarray:
         """
         The numpy array interface.
 

pandas/core/arrays/datetimelike.py

@@ -481,7 +481,7 @@ def _formatter(self, boxed=False):
     def nbytes(self):
         return self._data.nbytes
 
-    def __array__(self, dtype=None):
+    def __array__(self, dtype=None) -> np.ndarray:
         # used for Timedelta/DatetimeArray, overwritten by PeriodArray
         if is_object_dtype(dtype):
             return np.array(list(self), dtype=object)

pandas/core/arrays/datetimes.py

@@ -562,7 +562,7 @@ def _resolution(self):
     # ----------------------------------------------------------------
     # Array-Like / EA-Interface Methods
 
-    def __array__(self, dtype=None):
+    def __array__(self, dtype=None) -> np.ndarray:
         if dtype is None and self.tz:
             # The default for tz-aware is object, to preserve tz info
             dtype = object

pandas/core/arrays/interval.py

@@ -1063,7 +1063,7 @@ def is_non_overlapping_monotonic(self):
         )
 
     # Conversion
-    def __array__(self, dtype=None):
+    def __array__(self, dtype=None) -> np.ndarray:
         """
         Return the IntervalArray's data as a numpy array of Interval
         objects (with dtype='object')

pandas/core/arrays/masked.py

@@ -136,7 +136,7 @@ def to_numpy(
 
     __array_priority__ = 1000  # higher than ndarray so ops dispatch to us
 
-    def __array__(self, dtype=None):
+    def __array__(self, dtype=None) -> np.ndarray:
         """
         the array interface, return my values
         We return an object array here to preserve our scalar values

pandas/core/arrays/numpy_.py

@@ -182,7 +182,7 @@ def dtype(self):
     # ------------------------------------------------------------------------
     # NumPy Array Interface
 
-    def __array__(self, dtype=None):
+    def __array__(self, dtype=None) -> np.ndarray:
         return np.asarray(self._ndarray, dtype=dtype)
 
     _HANDLED_TYPES = (np.ndarray, numbers.Number)

pandas/core/arrays/period.py

@@ -279,7 +279,7 @@ def freq(self):
         """
         return self.dtype.freq
 
-    def __array__(self, dtype=None):
+    def __array__(self, dtype=None) -> np.ndarray:
         # overriding DatetimelikeArray
         return np.array(list(self), dtype=object)
 

pandas/core/arrays/sparse/array.py

@@ -427,7 +427,7 @@ def from_spmatrix(cls, data):
 
         return cls._simple_new(arr, index, dtype)
 
-    def __array__(self, dtype=None, copy=True):
+    def __array__(self, dtype=None, copy=True) -> np.ndarray:
         fill_value = self.fill_value
 
         if self.sp_index.ngaps == 0:

pandas/core/generic.py

@@ -1882,7 +1882,7 @@ def empty(self) -> bool_t:
     # GH#23114 Ensure ndarray.__op__(DataFrame) returns NotImplemented
     __array_priority__ = 1000
 
-    def __array__(self, dtype=None):
+    def __array__(self, dtype=None) -> np.ndarray:
         return com.values_from_object(self)
 
     def __array_wrap__(self, result, context=None):

pandas/core/indexes/base.py

@@ -597,7 +597,7 @@ def __len__(self) -> int:
         """
         return len(self._data)
 
-    def __array__(self, dtype=None):
+    def __array__(self, dtype=None) -> np.ndarray:
         """
         The array interface, return my values.
         """

pandas/core/indexes/category.py

@@ -392,7 +392,7 @@ def __contains__(self, key) -> bool:
 
         return contains(self, key, container=self._engine)
 
-    def __array__(self, dtype=None):
+    def __array__(self, dtype=None) -> np.ndarray:
         """ the array interface, return my values """
         return np.array(self._data, dtype=dtype)
 

pandas/core/indexes/datetimes.py

@@ -294,7 +294,7 @@ def _simple_new(cls, values, name=None, freq=None, tz=None, dtype=None):
 
     # --------------------------------------------------------------------
 
-    def __array__(self, dtype=None):
+    def __array__(self, dtype=None) -> np.ndarray:
         return np.asarray(self._data, dtype=dtype)
 
     @cache_readonly

pandas/core/indexes/multi.py

@@ -951,7 +951,7 @@ def copy(
             _set_identity=_set_identity,
         )
 
-    def __array__(self, dtype=None):
+    def __array__(self, dtype=None) -> np.ndarray:
         """ the array interface, return my values """
         return self.values
 

pandas/core/indexes/period.py

@@ -391,7 +391,7 @@ def _int64index(self):
     # ------------------------------------------------------------------------
     # Index Methods
 
-    def __array__(self, dtype=None):
+    def __array__(self, dtype=None) -> np.ndarray:
         if is_integer_dtype(dtype):
             return self.asi8
         else:

pandas/core/series.py

@@ -670,7 +670,7 @@ def construct_return(result):
         else:
             return construct_return(result)
 
-    def __array__(self, dtype=None):
+    def __array__(self, dtype=None) -> np.ndarray:
         """
         Return the values as a NumPy array.
 

pandas/tests/indexes/test_base.py

@@ -245,7 +245,7 @@ class ArrayLike:
             def __init__(self, array):
                 self.array = array
 
-            def __array__(self, dtype=None):
+            def __array__(self, dtype=None) -> np.ndarray:
                 return self.array
 
         expected = pd.Index(array)