modified test_searchsorted, discarded the use of numpy.testing

Author: GSAUC3

.gitignore

@@ -142,4 +142,4 @@ doc/source/savefig/
 ##############################
 /.pyodide-xbuildenv-*
 
-*.ipynb 
+*.ipynb

pandas/core/indexes/multi.py

@@ -3778,7 +3778,6 @@ def _reorder_indexer(
         ind = np.lexsort(keys)
         return indexer[ind]
 
-
     def searchsorted(
         self,
         value: tuple[Hashable, ...],
@@ -3814,39 +3813,47 @@ def searchsorted(
         >>> mi.searchsorted(("b", "y"))
         1
         """
-        if not isinstance(value, (tuple,list)):   
+        if not isinstance(value, (tuple, list)):
             raise TypeError("value must be a tuple or list")
 
         if isinstance(value, tuple):
             value = [value]
         if side not in ["left", "right"]:
             raise ValueError("side must be either 'left' or 'right'")
-        
+
         if not value:
             raise ValueError("searchsorted requires a non-empty value")
-        
-        try: 
-  
+
+        try:
             indexer = self.get_indexer(value)
             result = []
 
             for v, i in zip(value, indexer):
-                if i!= -1:
+                if i != -1:
                     result.append(i if side == "left" else i + 1)
-                else: 
-                    dtype = np.dtype([(f"level_{i}", level.dtype) for i, level in enumerate(self.levels)])
+                else:
+                    dtype = np.dtype(
+                        [
+                            (f"level_{i}", level.dtype)
+                            for i, level in enumerate(self.levels)
+                        ]
+                    )
 
                     val_array = np.array(value, dtype=dtype)
-                    
-                    pos = np.searchsorted( np.asarray(self.values,dtype=dtype),val_array , side=side, sorter = sorter)
+
+                    pos = np.searchsorted(
+                        np.asarray(self.values, dtype=dtype),
+                        val_array,
+                        side=side,
+                        sorter=sorter,
+                    )
                     result.append(pos)
-            
+
             return np.array(result, dtype=np.intp)
 
         except KeyError:
             pass
 
-
     def truncate(self, before=None, after=None) -> MultiIndex:
         """
         Slice index between two labels / tuples, return new MultiIndex.
@@ -4406,6 +4413,3 @@ def cartesian_product(X: list[np.ndarray]) -> list[np.ndarray]:
         )
         for i, x in enumerate(X)
     ]
-
-
-

pandas/tests/indexes/multi/test_indexing.py

@@ -1031,38 +1031,27 @@ def test_get_loc_namedtuple_behaves_like_tuple():
         assert idx.get_loc(("i5", "i6")) == 2
 
 
+def test_searchsorted():
+    mi = MultiIndex.from_tuples([("a", 0), ("a", 1), 
+                                 ("b", 0), ("b", 1), ("c", 0)])
 
+    assert mi.searchsorted(("b", 0)) == 2
+    assert mi.searchsorted(("b", 0), side="right") == 3
 
-def test_searchsorted():
-    mi = MultiIndex.from_tuples([
-        ('a', 0),
-        ('a', 1),
-        ('b', 0),
-        ('b', 1),
-        ('c', 0)
-    ])
-
-    
-    assert mi.searchsorted(('b', 0)) == 2
-    assert mi.searchsorted(('b', 0), side="right") == 3
-    
-    assert mi.searchsorted(('a', 0)) == 0
-    assert mi.searchsorted(('a', -1)) == 0
-    assert mi.searchsorted(('c', 1)) == 5  # Beyond the last
-
-    
-    result = mi.searchsorted([('a', 1), ('b', 0), ('c', 0)])
+    assert mi.searchsorted(("a", 0)) == 0
+    assert mi.searchsorted(("a", -1)) == 0
+    assert mi.searchsorted(("c", 1)) == 5  # Beyond the last
+
+    result = mi.searchsorted([("a", 1), ("b", 0), ("c", 0)])
     expected = np.array([1, 2, 4], dtype=np.intp)
-    np.testing.assert_array_equal(result, expected)
+    tm.assert_numpy_array_equal(result, expected)
 
-    
-    result = mi.searchsorted([('a', 1), ('b', 0), ('c', 0)], side='right')
+    result = mi.searchsorted([("a", 1), ("b", 0), ("c", 0)], side="right")
     expected = np.array([2, 3, 5], dtype=np.intp)
-    np.testing.assert_array_equal(result, expected)
+    tm.assert_numpy_array_equal(result, expected)
 
-    
     with pytest.raises(ValueError, match="side must be either 'left' or 'right'"):
-        mi.searchsorted(('a', 1), side='middle')
- 
+        mi.searchsorted(("a", 1), side="middle")
+
     with pytest.raises(TypeError, match="value must be a tuple or list"):
-        mi.searchsorted('a')  # not a tuple
+        mi.searchsorted("a")  # not a tuple