diff --git a/test/arrays_test.py b/test/arrays_test.py
index 0f9775cda..106d72337 100644
--- a/test/arrays_test.py
+++ b/test/arrays_test.py
@@ -75,34 +75,25 @@ class ArraysDistTest(unittest.TestCase):
     services.start_singlenode_cluster(return_drivers=False, num_objstores=2, num_workers_per_objstore=5, worker_path=worker_path)
 
     x = da.zeros([9, 25, 51], "float")
-    y = da.assemble(x)
-    self.assertTrue(np.alltrue(ray.pull(y) == np.zeros([9, 25, 51])))
+    self.assertTrue(np.alltrue(ray.pull(da.assemble(x)) == np.zeros([9, 25, 51])))
 
     x = da.ones([11, 25, 49], dtype_name="float")
-    y = da.assemble(x)
-    self.assertTrue(np.alltrue(ray.pull(y) == np.ones([11, 25, 49])))
+    self.assertTrue(np.alltrue(ray.pull(da.assemble(x)) == np.ones([11, 25, 49])))
 
     x = da.random.normal([11, 25, 49])
     y = da.copy(x)
-    z = da.assemble(x)
-    w = da.assemble(y)
-    self.assertTrue(np.alltrue(ray.pull(z) == ray.pull(w)))
+    self.assertTrue(np.alltrue(ray.pull(da.assemble(x)) == ray.pull(da.assemble(y))))
 
     x = da.eye(25, dtype_name="float")
-    y = da.assemble(x)
-    self.assertTrue(np.alltrue(ray.pull(y) == np.eye(25)))
+    self.assertTrue(np.alltrue(ray.pull(da.assemble(x)) == np.eye(25)))
 
     x = da.random.normal([25, 49])
     y = da.triu(x)
-    z = da.assemble(y)
-    w = da.assemble(x)
-    self.assertTrue(np.alltrue(ray.pull(z) == np.triu(ray.pull(w))))
+    self.assertTrue(np.alltrue(ray.pull(da.assemble(y)) == np.triu(ray.pull(da.assemble(x)))))
 
     x = da.random.normal([25, 49])
     y = da.tril(x)
-    z = da.assemble(y)
-    w = da.assemble(x)
-    self.assertTrue(np.alltrue(ray.pull(z) == np.tril(ray.pull(w))))
+    self.assertTrue(np.alltrue(ray.pull(da.assemble(y)) == np.tril(ray.pull(da.assemble(x)))))
 
     x = da.random.normal([25, 49])
     y = da.random.normal([49, 18])
@@ -117,35 +108,25 @@ class ArraysDistTest(unittest.TestCase):
     x = da.random.normal([23, 42])
     y = da.random.normal([23, 42])
     z = da.add(x, y)
-    z_full = da.assemble(z)
-    x_full = da.assemble(x)
-    y_full = da.assemble(y)
-    self.assertTrue(np.allclose(ray.pull(z_full), ray.pull(x_full) + ray.pull(y_full)))
+    self.assertTrue(np.allclose(ray.pull(da.assemble(z)), ray.pull(da.assemble(x)) + ray.pull(da.assemble(y))))
 
     # test subtract
     x = da.random.normal([33, 40])
     y = da.random.normal([33, 40])
     z = da.subtract(x, y)
-    z_full = da.assemble(z)
-    x_full = da.assemble(x)
-    y_full = da.assemble(y)
-    self.assertTrue(np.allclose(ray.pull(z_full), ray.pull(x_full) - ray.pull(y_full)))
+    self.assertTrue(np.allclose(ray.pull(da.assemble(z)), ray.pull(da.assemble(x)) - ray.pull(da.assemble(y))))
 
     # test transpose
     x = da.random.normal([234, 432])
     y = da.transpose(x)
-    x_full = da.assemble(x)
-    y_full = da.assemble(y)
-    self.assertTrue(np.alltrue(ray.pull(x_full).T == ray.pull(y_full)))
+    self.assertTrue(np.alltrue(ray.pull(da.assemble(x)).T == ray.pull(da.assemble(y))))
 
     # test numpy_to_dist
     x = da.random.normal([23, 45])
     y = da.assemble(x)
     z = da.numpy_to_dist(y)
     w = da.assemble(z)
-    x_full = da.assemble(x)
-    z_full = da.assemble(z)
-    self.assertTrue(np.alltrue(ray.pull(x_full) == ray.pull(z_full)))
+    self.assertTrue(np.alltrue(ray.pull(da.assemble(x)) == ray.pull(da.assemble(z))))
     self.assertTrue(np.alltrue(ray.pull(y) == ray.pull(w)))
 
     # test da.tsqr
@@ -153,10 +134,8 @@ class ArraysDistTest(unittest.TestCase):
       x = da.random.normal(shape)
       K = min(shape)
       q, r = da.linalg.tsqr(x)
-      x_full = da.assemble(x)
-      x_val = ray.pull(x_full)
-      q_full = da.assemble(q)
-      q_val = ray.pull(q_full)
+      x_val = ray.pull(da.assemble(x))
+      q_val = ray.pull(da.assemble(q))
       r_val = ray.pull(r)
       self.assertTrue(r_val.shape == (K, shape[1]))
       self.assertTrue(np.alltrue(r_val == np.triu(r_val)))
@@ -173,8 +152,7 @@ class ArraysDistTest(unittest.TestCase):
       l, u, s = da.linalg.modified_lu(da.numpy_to_dist(q))
       q_val = ray.pull(q)
       r_val = ray.pull(r)
-      l_full = da.assemble(l)
-      l_val = ray.pull(l_full)
+      l_val = ray.pull(da.assemble(l))
       u_val = ray.pull(u)
       s_val = ray.pull(s)
       s_mat = np.zeros((d1, d2))
@@ -192,10 +170,8 @@ class ArraysDistTest(unittest.TestCase):
       print "testing dist_tsqr_hr with d1 = " + str(d1) + ", d2 = " + str(d2)
       a = da.random.normal([d1, d2])
       y, t, y_top, r = da.linalg.tsqr_hr(a)
-      a_full = da.assemble(a)
-      a_val = ray.pull(a_full)
-      y_full = da.assemble(y)
-      y_val = ray.pull(y_full)
+      a_val = ray.pull(da.assemble(a))
+      y_val = ray.pull(da.assemble(y))
       t_val = ray.pull(t)
       y_top_val = ray.pull(y_top)
       r_val = ray.pull(r)
@@ -213,13 +189,9 @@ class ArraysDistTest(unittest.TestCase):
       a = da.random.normal([d1, d2])
       K = min(d1, d2)
       q, r = da.linalg.qr(a)
-      a_full = da.assemble(a)
-      q_full = da.assemble(q)
-      r_full = da.assemble(r)
-      a_val = ray.pull(a_full)
-      q_val = ray.pull(q_full)
-      r_val = ray.pull(r_full)
-
+      a_val = ray.pull(da.assemble(a))
+      q_val = ray.pull(da.assemble(q))
+      r_val = ray.pull(da.assemble(r))
       self.assertTrue(q_val.shape == (d1, K))
       self.assertTrue(r_val.shape == (K, d2))
       self.assertTrue(np.allclose(np.dot(q_val.T, q_val), np.eye(K)))