annotations

pandas/_libs/interval.pyx

@@ -326,7 +326,7 @@ cdef class Interval(IntervalMixin):
     def __hash__(self):
         return hash((self.left, self.right, self.closed))
 
-    def __contains__(self, key):
+    def __contains__(self, key) -> bool:
         if _interval_like(key):
             raise TypeError("__contains__ not defined for two intervals")
         return ((self.left < key if self.open_left else self.left <= key) and

pandas/core/arrays/categorical.py

@@ -1874,7 +1874,7 @@ def __iter__(self):
         """
         return iter(self._internal_get_values().tolist())
 
-    def __contains__(self, key):
+    def __contains__(self, key) -> bool:
         """
         Returns True if `key` is in this Categorical.
         """
@@ -1884,7 +1884,7 @@ def __contains__(self, key):
 
         return contains(self, key, container=self._codes)
 
-    def _tidy_repr(self, max_vals=10, footer=True):
+    def _tidy_repr(self, max_vals=10, footer=True) -> str:
         """ a short repr displaying only max_vals and an optional (but default
         footer)
         """
@@ -1921,7 +1921,7 @@ def _repr_categories(self):
         category_strs = [x.strip() for x in category_strs]
         return category_strs
 
-    def _repr_categories_info(self):
+    def _repr_categories_info(self) -> str:
         """
         Returns a string representation of the footer.
         """
@@ -1951,11 +1951,11 @@ def _repr_categories_info(self):
         # replace to simple save space by
         return levheader + "[" + levstring.replace(" < ... < ", " ... ") + "]"
 
-    def _repr_footer(self):
+    def _repr_footer(self) -> str:
         info = self._repr_categories_info()
         return f"Length: {len(self)}\n{info}"
 
-    def _get_repr(self, length=True, na_rep="NaN", footer=True):
+    def _get_repr(self, length=True, na_rep="NaN", footer=True) -> str:
         from pandas.io.formats import format as fmt
 
         formatter = fmt.CategoricalFormatter(

pandas/core/indexes/datetimelike.py

@@ -147,7 +147,7 @@ def __array_wrap__(self, result, context=None):
 
     # ------------------------------------------------------------------------
 
-    def equals(self, other):
+    def equals(self, other) -> bool:
         """
         Determines if two Index objects contain the same elements.
         """

pandas/core/internals/managers.py

@@ -738,16 +738,16 @@ def combine(self, blocks, copy=True):
 
         return type(self)(new_blocks, axes, do_integrity_check=False)
 
-    def get_slice(self, slobj, axis=0):
+    def get_slice(self, slobj: slice, axis: int = 0):
         if axis >= self.ndim:
             raise IndexError("Requested axis not found in manager")
 
         if axis == 0:
             new_blocks = self._slice_take_blocks_ax0(slobj)
         else:
-            slicer = [slice(None)] * (axis + 1)
-            slicer[axis] = slobj
-            slicer = tuple(slicer)
+            _slicer = [slice(None)] * (axis + 1)
+            _slicer[axis] = slobj
+            slicer = tuple(_slicer)
             new_blocks = [blk.getitem_block(slicer) for blk in self.blocks]
 
         new_axes = list(self.axes)
@@ -757,11 +757,11 @@ def get_slice(self, slobj, axis=0):
         bm._consolidate_inplace()
         return bm
 
-    def __contains__(self, item):
+    def __contains__(self, item) -> bool:
         return item in self.items
 
     @property
-    def nblocks(self):
+    def nblocks(self) -> int:
         return len(self.blocks)
 
     def copy(self, deep=True):

pandas/plotting/_misc.py

@@ -453,7 +453,7 @@ def __delitem__(self, key):
             raise ValueError(f"Cannot remove default parameter {key}")
         return super().__delitem__(key)
 
-    def __contains__(self, key):
+    def __contains__(self, key) -> bool:
         key = self._get_canonical_key(key)
         return super().__contains__(key)
 

pandas/tests/dtypes/test_inference.py

@@ -240,7 +240,7 @@ def __getitem__(self, key):
 
         if has_contains:
 
-            def __contains__(self, key):
+            def __contains__(self, key) -> bool:
                 return self.d.__contains__(key)
 
     d = DictLike({1: 2})

pandas/tests/frame/methods/test_to_records.py

@@ -326,7 +326,7 @@ def __init__(self, **kwargs):
             def __getitem__(self, key):
                 return self.d.__getitem__(key)
 
-            def __contains__(self, key):
+            def __contains__(self, key) -> bool:
                 return key in self.d
 
             def keys(self):