diff --git a/sdks/python/apache_beam/examples/complete/distribopt.py b/sdks/python/apache_beam/examples/complete/distribopt.py
index 89c312fcbf5e..304a89cd100b 100644
--- a/sdks/python/apache_beam/examples/complete/distribopt.py
+++ b/sdks/python/apache_beam/examples/complete/distribopt.py
@@ -221,13 +221,28 @@ def _optimize_production_parameters(sim):
 
       # Run L-BFGS-B optimizer
       result = minimize(lambda x: np.sum(sim.simulate(x)), x0, bounds=bounds)
-      return result.x.tolist(), sim.simulate(result.x)
+
+      # Ensure result.x is always a list, regardless of NumPy version
+      x_values = result.x if isinstance(result.x, list) else result.x.tolist()
+
+      # Ensure simulation output is also properly converted
+      costs = sim.simulate(result.x)
+      costs = costs if isinstance(costs, list) else costs.tolist()
+
+      return x_values, costs
 
     def process(self, element):
       mapping_identifier, greenhouse = element[0]
       crops, quantities = zip(*element[1])
       sim = Simulator(quantities)
       optimum, costs = self._optimize_production_parameters(sim)
+
+      # Ensure NumPy arrays are converted to lists before yielding
+      if isinstance(optimum, np.ndarray):
+        optimum = optimum.tolist()
+      if isinstance(costs, np.ndarray):
+        costs = costs.tolist()
+
       solution = (mapping_identifier, (greenhouse, optimum))
       yield pvalue.TaggedOutput('solution', solution)
       for crop, cost, quantity in zip(crops, costs, quantities):
diff --git a/sdks/python/apache_beam/examples/complete/distribopt_test.py b/sdks/python/apache_beam/examples/complete/distribopt_test.py
index b9d507410267..a7b02d6a25d2 100644
--- a/sdks/python/apache_beam/examples/complete/distribopt_test.py
+++ b/sdks/python/apache_beam/examples/complete/distribopt_test.py
@@ -77,8 +77,11 @@ def test_basics(self):
     # Only 1 result
     self.assertEqual(len(lines), 1)
 
+    # Handle NumPy string representation before parsing
+    cleaned_line = lines[0].replace("np.str_('", "'").replace("')", "'")
+
     # parse result line and verify optimum
-    optimum = make_tuple(lines[0])
+    optimum = make_tuple(cleaned_line)
     self.assertAlmostEqual(optimum['cost'], 454.39597, places=3)
     self.assertDictEqual(optimum['mapping'], EXPECTED_MAPPING)
     production = optimum['production']