@@ -0,0 +1,6 @@
+Fix parfor variable hoisting analysis.
+--------------------------------------
+
+If a variable is used to build a container (e.g., tuple, list, map, set) or is passed as an
+argument to a call then conservatively assume it could escape the current iteration of
+the parfor and so should not be hoisted.
@@ -922,6 +922,20 @@ def find_setitems_block(setitems, itemsset, block, typemap):
         elif isinstance(inst, parfor.Parfor):
             find_setitems_block(setitems, itemsset, inst.init_block, typemap)
             find_setitems_body(setitems, itemsset, inst.loop_body, typemap)
+        elif isinstance(inst, ir.Assign):
+            # If something of mutable type is given to a build_tuple or
+            # used in a call then consider it unanalyzable and so
+            # unavailable for hoisting.
+            rhs = inst.value
+            if isinstance(rhs, ir.Expr):
+                if rhs.op in ["build_tuple", "build_list", "build_set", "build_map"]:
+                    for item in rhs.items:
+                        if getattr(typemap[item.name], "mutable", False):
+                            itemsset.add(item.name)
+                elif rhs.op == "call":
+                    for item in list(rhs.args) + [x[1] for x in rhs.kws]:
+                        if getattr(typemap[item.name], "mutable", False):
+                            itemsset.add(item.name)
 
 def find_setitems_body(setitems, itemsset, loop_body, typemap):
     """
 
@@ -29,6 +29,8 @@
                    set_num_threads, get_num_threads, typeof)
 from numba.core import (types, errors, ir, rewrites,
                         typed_passes, inline_closurecall, config, compiler, cpu)
+from numba.typed import Dict, List
+
 from numba.extending import (overload_method, register_model,
                              typeof_impl, unbox, NativeValue, models)
 from numba.core.registry import cpu_target
@@ -230,6 +232,10 @@ def copy_args(*args):
                     new_args.append(copy.deepcopy(x))
                 elif isinstance(x, list):
                     new_args.append(x[:])
+                elif isinstance(x, Dict):
+                    new_args.append(copy.copy(x))
+                elif isinstance(x, List):
+                    new_args.append(copy.copy(x))
                 else:
                     raise ValueError('Unsupported argument type encountered')
             return tuple(new_args)
@@ -4082,6 +4088,11 @@ def test_impl(x, par, numthreads):
         self.prange_tester(test_impl, x, par, 2)
 
 
+@register_jitable
+def test_call_hoisting_outcall(a,b):
+    return (a, b)
+
+
 @skip_parfors_unsupported
 class TestPrangeSpecific(TestPrangeBase):
     """ Tests specific features/problems found under prange"""
@@ -4421,6 +4432,34 @@ def test_impl():
 
         self.prange_tester(test_impl)
 
+    def test_tuple_hoisting(self):
+        # issue9529
+        def test_impl(inputs):
+            outputs = [(Dict.empty(key_type=types.int64, value_type=types.float64), np.zeros(1)) for _ in range(len(inputs))]
+            for i in range(len(inputs)):
+                y = inputs[i]
+                out = np.zeros(1)
+                out[0] = i
+                outputs[i] = (inputs[i], out)
+            return outputs[0][1][0]
+
+        N = config.NUMBA_NUM_THREADS + 1
+        self.prange_tester(test_impl, [Dict.empty(key_type=types.int64, value_type=types.float64) for i in range(N)])
+
+    def test_call_hoisting(self):
+        # issue9529
+        def test_impl(inputs):
+            outputs = [(Dict.empty(key_type=types.int64, value_type=types.float64), np.zeros(1)) for _ in range(len(inputs))]
+            for i in range(len(inputs)):
+                y = inputs[i]
+                out = np.zeros(1)
+                out[0] = i
+                outputs[i] = test_call_hoisting_outcall(inputs[i], out)
+            return outputs[0][1][0]
+
+        N = config.NUMBA_NUM_THREADS + 1
+        self.prange_tester(test_impl, [Dict.empty(key_type=types.int64, value_type=types.float64) for i in range(N)])
+
     def test_record_array_setitem(self):
         # issue6704
         state_dtype = np.dtype([('var', np.int32)])