Fix python linting (#2076)

test/actor_test.py

@@ -1038,14 +1038,14 @@ class ActorsWithGPUs(unittest.TestCase):
         def locations_to_intervals_for_many_tasks():
             # Launch a bunch of GPU tasks.
             locations_ids_and_intervals = ray.get([
-                f1.remote() for _ in range(
-                    5 * num_local_schedulers * num_gpus_per_scheduler)
+                f1.remote() for _ in range(5 * num_local_schedulers *
+                                           num_gpus_per_scheduler)
             ] + [
-                f2.remote() for _ in range(
-                    5 * num_local_schedulers * num_gpus_per_scheduler)
+                f2.remote() for _ in range(5 * num_local_schedulers *
+                                           num_gpus_per_scheduler)
             ] + [
-                f1.remote() for _ in range(
-                    5 * num_local_schedulers * num_gpus_per_scheduler)
+                f1.remote() for _ in range(5 * num_local_schedulers *
+                                           num_gpus_per_scheduler)
             ])
 
             locations_to_intervals = collections.defaultdict(lambda: [])
@@ -1108,8 +1108,9 @@ class ActorsWithGPUs(unittest.TestCase):
 
         # Create more actors to fill up all the GPUs.
         more_actors = [
-            Actor1.remote() for _ in range(
-                num_local_schedulers * num_gpus_per_scheduler - 1 - 3)
+            Actor1.remote()
+            for _ in range(num_local_schedulers * num_gpus_per_scheduler - 1 -
+                           3)
         ]
         # Wait for the actors to finish being created.
         ray.get([actor.get_location_and_ids.remote() for actor in more_actors])

test/array_test.py

@@ -67,11 +67,12 @@ class DistributedArrayTest(unittest.TestCase):
         b = ra.zeros.remote([da.BLOCK_SIZE, da.BLOCK_SIZE])
         x = da.DistArray([2 * da.BLOCK_SIZE, da.BLOCK_SIZE],
                          np.array([[a], [b]]))
-        assert_equal(x.assemble(),
-                     np.vstack([
-                         np.ones([da.BLOCK_SIZE, da.BLOCK_SIZE]),
-                         np.zeros([da.BLOCK_SIZE, da.BLOCK_SIZE])
-                     ]))
+        assert_equal(
+            x.assemble(),
+            np.vstack([
+                np.ones([da.BLOCK_SIZE, da.BLOCK_SIZE]),
+                np.zeros([da.BLOCK_SIZE, da.BLOCK_SIZE])
+            ]))
 
     def testMethods(self):
         for module in [

test/failure_test.py

@@ -387,9 +387,8 @@ class PutErrorTest(unittest.TestCase):
             # on the one before it. The result of the first task should get
             # evicted.
             args = []
-            arg = single_dependency.remote(0,
-                                           np.zeros(
-                                               object_size, dtype=np.uint8))
+            arg = single_dependency.remote(
+                0, np.zeros(object_size, dtype=np.uint8))
             for i in range(num_objects):
                 arg = single_dependency.remote(i, arg)
                 args.append(arg)

test/runtest.py

@@ -180,12 +180,10 @@ LIST_OBJECTS = [[obj] for obj in BASE_OBJECTS]
 TUPLE_OBJECTS = [(obj, ) for obj in BASE_OBJECTS]
 # The check that type(obj).__module__ != "numpy" should be unnecessary, but
 # otherwise this seems to fail on Mac OS X on Travis.
-DICT_OBJECTS = (
-    [{
-        obj: obj
-    } for obj in PRIMITIVE_OBJECTS
-     if (obj.__hash__ is not None and type(obj).__module__ != "numpy")] +
-    [{
+DICT_OBJECTS = ([{
+    obj: obj
+} for obj in PRIMITIVE_OBJECTS if (
+    obj.__hash__ is not None and type(obj).__module__ != "numpy")] + [{
         0: obj
     } for obj in BASE_OBJECTS] + [{
         Foo(123): Foo(456)