Closes #5155: Bug: MultiIndex .lookup() attempts illegal dtype cast for tuple keys

arkouda/pandas/index.py

@@ -72,13 +72,12 @@
 
 from arkouda.numpy.dtypes import bool_ as akbool
 from arkouda.numpy.dtypes import bool_scalars
-from arkouda.numpy.dtypes import int64 as akint64
 from arkouda.numpy.manipulation_functions import flip as ak_flip
 from arkouda.numpy.pdarrayclass import RegistrationError, pdarray
 from arkouda.numpy.pdarraysetops import argsort, in1d
 from arkouda.numpy.sorting import coargsort
 from arkouda.numpy.util import convert_if_categorical, generic_concat, get_callback
-from arkouda.pandas.groupbyclass import GroupBy, unique
+from arkouda.pandas.groupbyclass import GroupBy, groupable, unique
 
 
 __all__ = [
@@ -1202,12 +1201,13 @@ def lookup(self, key):
         Returns
         -------
         pdarray
-            A boolean array indicating which elements of `key` are present in the Index.
+            A boolean array of length ``len(self)``, indicating which entries of
+            the Index are present in `key`.
 
         Raises
         ------
         TypeError
-            If `key` is not a scalar or a pdarray.
+            If `key` cannot be converted to an arkouda array.
 
         """
         from arkouda.numpy.pdarrayclass import pdarray
@@ -2139,15 +2139,22 @@ def concat(self, other):
         idx = [generic_concat([ix1, ix2], ordered=True) for ix1, ix2 in zip(self.index, other.index)]
         return MultiIndex(idx)
 
-    def lookup(self, key):
+    def lookup(self, key: Union[List, Tuple]) -> groupable:
         """
         Perform element-wise lookup on the MultiIndex.
 
         Parameters
         ----------
         key : list or tuple
-            A sequence of values, one for each level of the MultiIndex. Values may be scalars
-            or pdarrays. If scalars, they are cast to the appropriate Arkouda array type.
+            A sequence of values, one for each level of the MultiIndex.
+
+            - If the elements are scalars (e.g., ``(1, "red")``), they are
+              treated as a single row key: the result is a boolean mask over
+              rows where all levels match the corresponding scalar.
+            - If the elements are arkouda arrays (e.g., list of pdarrays /
+              Strings), they must align one-to-one with the levels, and the
+              lookup is delegated to ``in1d(self.index, key)`` for multi-column
+              membership.
 
         Returns
         -------
@@ -2157,21 +2164,41 @@ def lookup(self, key):
         Raises
         ------
         TypeError
-            If `key` is not a list or tuple, or if its elements cannot be converted to pdarrays.
+            If `key` is not a list or tuple.
+        ValueError
+            If the length of `key` does not match the number of levels.
 
         """
-        from arkouda.numpy import cast as akcast
         from arkouda.numpy.pdarrayclass import pdarray
         from arkouda.numpy.pdarraycreation import array
+        from arkouda.numpy.strings import Strings
+
+        if not isinstance(key, (list, tuple)):
+            raise TypeError("MultiIndex.lookup expects a list or tuple of keys, one per level")
+
+        if len(key) != self.nlevels:
+            raise ValueError(
+                f"MultiIndex.lookup key length {len(key)} must match number of levels {self.nlevels}"
+            )
+
+        # Case 1: user passed per-level arkouda arrays.
+        # We assume they are already the correct types and lengths.
+        if isinstance(key[0], (pdarray, Strings)):
+            return in1d(self.index, key)
+
+        # Case 2: user passed scalars (e.g., (1, "red")).
+        # Convert each scalar to a length-1 arkouda array, preserving per-level dtypes.
+        scalar_key_arrays = []
+        for i, v in enumerate(key):
+            lvl = self.levels[i]
+
+            # Determine the dtype for this level
+            dt = lvl.dtype
 
-        if not isinstance(key, list) and not isinstance(key, tuple):
-            raise TypeError("MultiIndex lookup failure")
-        # if individual vals convert to pdarrays
-        if not isinstance(key[0], pdarray):
-            dt = self.levels[0].dtype if isinstance(self.levels[0], pdarray) else akint64
-            key = [akcast(array([x]), dt) for x in key]
+            a = array([v], dtype=dt)  # make length-1 array
+            scalar_key_arrays.append(a)
 
-        return in1d(self.index, key)
+        return in1d(self.index, scalar_key_arrays)
 
     def to_hdf(
         self,

tests/pandas/index_test.py

@@ -846,3 +846,17 @@ def test_round_trip_conversion_categorical(self, size):
         i1 = ak.Index(ak.Categorical(strings1))
         i2 = ak.Index(i1.to_pandas())
         assert_index_equal(i1, i2)
+
+    def test_multiindex_lookup_tuple_mixed_dtypes(self):
+        # Level 0: int
+        lvl0 = ak.array([1, 1, 2, 3])
+        # Level 1: strings
+        lvl1 = ak.array(["red", "blue", "red", "red"])
+
+        midx = ak.MultiIndex([lvl0, lvl1], names=["num", "color"])
+
+        # Tuple key mixes int + str and should NOT trigger castStringsTo<int64> on "red"
+        mask = midx.lookup((1, "red"))
+
+        # Expect exactly the first row to match
+        assert mask.to_ndarray().tolist() == [True, False, False, False]