TYP: annotations in indexes (#31181)

Author: jbrockmendel

pandas/core/base.py

@@ -3,7 +3,7 @@
 """
 import builtins
 import textwrap
-from typing import Dict, FrozenSet, List, Optional
+from typing import Dict, FrozenSet, List, Optional, Union
 
 import numpy as np
 
@@ -110,7 +110,7 @@ def _freeze(self):
         object.__setattr__(self, "__frozen", True)
 
     # prevent adding any attribute via s.xxx.new_attribute = ...
-    def __setattr__(self, key, value):
+    def __setattr__(self, key: str, value):
         # _cache is used by a decorator
         # We need to check both 1.) cls.__dict__ and 2.) getattr(self, key)
         # because
@@ -239,7 +239,7 @@ def __getitem__(self, key):
                 raise KeyError(f"Column not found: {key}")
             return self._gotitem(key, ndim=1)
 
-    def _gotitem(self, key, ndim, subset=None):
+    def _gotitem(self, key, ndim: int, subset=None):
         """
         sub-classes to define
         return a sliced object
@@ -605,6 +605,11 @@ class IndexOpsMixin:
         ["tolist"]  # tolist is not deprecated, just suppressed in the __dir__
     )
 
+    @property
+    def _values(self) -> Union[ExtensionArray, np.ndarray]:
+        # must be defined here as a property for mypy
+        raise AbstractMethodError(self)
+
     def transpose(self, *args, **kwargs):
         """
         Return the transpose, which is by definition self.
@@ -630,6 +635,10 @@ def shape(self):
         """
         return self._values.shape
 
+    def __len__(self) -> int:
+        # We need this defined here for mypy
+        raise AbstractMethodError(self)
+
     @property
     def ndim(self) -> int:
         """
@@ -664,14 +673,14 @@ def item(self):
             raise ValueError("can only convert an array of size 1 to a Python scalar")
 
     @property
-    def nbytes(self):
+    def nbytes(self) -> int:
         """
         Return the number of bytes in the underlying data.
         """
         return self._values.nbytes
 
     @property
-    def size(self):
+    def size(self) -> int:
         """
         Return the number of elements in the underlying data.
         """
@@ -1058,7 +1067,14 @@ def hasnans(self):
         return bool(isna(self).any())
 
     def _reduce(
-        self, op, name, axis=0, skipna=True, numeric_only=None, filter_type=None, **kwds
+        self,
+        op,
+        name: str,
+        axis=0,
+        skipna=True,
+        numeric_only=None,
+        filter_type=None,
+        **kwds,
     ):
         """ perform the reduction type operation if we can """
         func = getattr(self, name, None)
@@ -1254,7 +1270,7 @@ def unique(self):
 
         return result
 
-    def nunique(self, dropna=True):
+    def nunique(self, dropna: bool = True) -> int:
         """
         Return number of unique elements in the object.
 
@@ -1295,7 +1311,7 @@ def nunique(self, dropna=True):
         return n
 
     @property
-    def is_unique(self):
+    def is_unique(self) -> bool:
         """
         Return boolean if values in the object are unique.
 
@@ -1306,7 +1322,7 @@ def is_unique(self):
         return self.nunique(dropna=False) == len(self)
 
     @property
-    def is_monotonic(self):
+    def is_monotonic(self) -> bool:
         """
         Return boolean if values in the object are
         monotonic_increasing.
@@ -1319,7 +1335,11 @@ def is_monotonic(self):
 
         return Index(self).is_monotonic
 
-    is_monotonic_increasing = is_monotonic
+    @property
+    def is_monotonic_increasing(self) -> bool:
+        """alias for is_monotonic"""
+        # mypy complains if we alias directly
+        return self.is_monotonic
 
     @property
     def is_monotonic_decreasing(self) -> bool:
@@ -1472,7 +1492,7 @@ def factorize(self, sort=False, na_sentinel=-1):
 
     @Substitution(klass="Index")
     @Appender(_shared_docs["searchsorted"])
-    def searchsorted(self, value, side="left", sorter=None):
+    def searchsorted(self, value, side="left", sorter=None) -> np.ndarray:
         return algorithms.searchsorted(self._values, value, side=side, sorter=sorter)
 
     def drop_duplicates(self, keep="first", inplace=False):

pandas/core/common.py

@@ -178,35 +178,35 @@ def not_none(*args):
     return (arg for arg in args if arg is not None)
 
 
-def any_none(*args):
+def any_none(*args) -> bool:
     """
     Returns a boolean indicating if any argument is None.
     """
     return any(arg is None for arg in args)
 
 
-def all_none(*args):
+def all_none(*args) -> bool:
     """
     Returns a boolean indicating if all arguments are None.
     """
     return all(arg is None for arg in args)
 
 
-def any_not_none(*args):
+def any_not_none(*args) -> bool:
     """
     Returns a boolean indicating if any argument is not None.
     """
     return any(arg is not None for arg in args)
 
 
-def all_not_none(*args):
+def all_not_none(*args) -> bool:
     """
     Returns a boolean indicating if all arguments are not None.
     """
     return all(arg is not None for arg in args)
 
 
-def count_not_none(*args):
+def count_not_none(*args) -> int:
     """
     Returns the count of arguments that are not None.
     """
@@ -286,7 +286,7 @@ def maybe_iterable_to_list(obj: Union[Iterable[T], T]) -> Union[Collection[T], T
     return obj
 
 
-def is_null_slice(obj):
+def is_null_slice(obj) -> bool:
     """
     We have a null slice.
     """
@@ -306,7 +306,7 @@ def is_true_slices(l):
 
 
 # TODO: used only once in indexing; belongs elsewhere?
-def is_full_slice(obj, l):
+def is_full_slice(obj, l) -> bool:
     """
     We have a full length slice.
     """