BUG: TimedeltaIndex.searchsorted accepting invalid types/dtypes

pandas/core/indexes/timedeltas.py

@@ -357,11 +357,25 @@ def _partial_td_slice(self, key):
     @Appender(_shared_docs["searchsorted"])
     def searchsorted(self, value, side="left", sorter=None):
         if isinstance(value, (np.ndarray, Index)):
-            value = np.array(value, dtype=_TD_DTYPE, copy=False)
-        else:
-            value = Timedelta(value).asm8.view(_TD_DTYPE)
+            if not type(self._data)._is_recognized_dtype(value):
+                raise TypeError(
+                    "searchsorted requires compatible dtype or scalar, "
+                    f"not {type(value).__name__}"
+                )
+            value = type(self._data)(value)
+            self._data._check_compatible_with(value)
+
+        elif isinstance(value, self._data._recognized_scalars):
+            self._data._check_compatible_with(value)
+            value = self._data._scalar_type(value)
+
+        elif not isinstance(value, TimedeltaArray):
+            raise TypeError(
+                "searchsorted requires compatible dtype or scalar, "
+                f"not {type(value).__name__}"
+            )
 
-        return self.values.searchsorted(value, side=side, sorter=sorter)
+        return self._data.searchsorted(value, side=side, sorter=sorter)
 
     def is_type_compatible(self, typ) -> bool:
         return typ == self.inferred_type or typ == "timedelta"

pandas/tests/arrays/test_timedeltas.py

@@ -140,6 +140,42 @@ def test_setitem_objects(self, obj):
         arr[0] = obj
         assert arr[0] == pd.Timedelta(seconds=1)
 
+    @pytest.mark.parametrize(
+        "other",
+        [
+            1,
+            np.int64(1),
+            1.0,
+            np.datetime64("NaT"),
+            pd.Timestamp.now(),
+            "invalid",
+            np.arange(10, dtype="i8") * 24 * 3600 * 10 ** 9,
+            (np.arange(10) * 24 * 3600 * 10 ** 9).view("datetime64[ns]"),
+            pd.Timestamp.now().to_period("D"),
+        ],
+    )
+    @pytest.mark.parametrize(
+        "index",
+        [
+            True,
+            pytest.param(
+                False,
+                marks=pytest.mark.xfail(
+                    reason="Raises ValueError instead of TypeError", raises=ValueError
+                ),
+            ),
+        ],
+    )
+    def test_searchsorted_invalid_types(self, other, index):
+        data = np.arange(10, dtype="i8") * 24 * 3600 * 10 ** 9
+        arr = TimedeltaArray(data, freq="D")
+        if index:
+            arr = pd.Index(arr)
+
+        msg = "searchsorted requires compatible dtype or scalar"
+        with pytest.raises(TypeError, match=msg):
+            arr.searchsorted(other)
+
 
 class TestReductions:
     @pytest.mark.parametrize("name", ["sum", "std", "min", "max", "median"])