fix: lint

Author: pawelpaszki

tests/e2e/rayjob_existing_cluster_kind_test.py

@@ -10,6 +10,7 @@
 
 # This test creates a Ray Cluster and then submits a RayJob against the existing cluster on Kind Cluster
 
+
 @pytest.mark.kind
 class TestRayJobExistingClusterKind:
     def setup_method(self):
@@ -30,12 +31,13 @@ def test_rayjob_ray_cluster_sdk_kind_nvidia_gpu(self):
         self.setup_method()
         create_namespace(self)
         create_kueue_resources(self)
-        self.run_rayjob_against_existing_cluster_kind(accelerator="gpu", number_of_gpus=1)
+        self.run_rayjob_against_existing_cluster_kind(
+            accelerator="gpu", number_of_gpus=1
+        )
 
     def run_rayjob_against_existing_cluster_kind(
         self, accelerator, gpu_resource_name="nvidia.com/gpu", number_of_gpus=0
     ):
-
         cluster_name = "existing-cluster"
         cluster = Cluster(
             ClusterConfiguration(
@@ -63,21 +65,25 @@ def run_rayjob_against_existing_cluster_kind(
         print(f"✅ Ray cluster '{cluster_name}' is ready")
 
         # test RayJob submission against the existing cluster
-        self.assert_rayjob_submit_against_existing_cluster(cluster, accelerator, number_of_gpus)
+        self.assert_rayjob_submit_against_existing_cluster(
+            cluster, accelerator, number_of_gpus
+        )
 
         # Cleanup - manually tear down the cluster since job won't do it
         print("🧹 Cleaning up Ray cluster")
         cluster.down()
 
-    def assert_rayjob_submit_against_existing_cluster(self, cluster, accelerator, number_of_gpus):
+    def assert_rayjob_submit_against_existing_cluster(
+        self, cluster, accelerator, number_of_gpus
+    ):
         """
         Test RayJob submission against an existing Ray cluster.
         """
         cluster_name = cluster.config.name
         job_name = f"mnist-rayjob-{accelerator}"
-        
+
         print(f"🚀 Testing RayJob submission against existing cluster '{cluster_name}'")
-        
+
         # Create RayJob targeting the existing cluster
         rayjob = RayJob(
             job_name=job_name,
@@ -94,7 +100,9 @@ def assert_rayjob_submit_against_existing_cluster(self, cluster, accelerator, nu
 
         # Submit the job
         submission_result = rayjob.submit()
-        assert submission_result == job_name, f"Job submission failed, expected {job_name}, got {submission_result}"
+        assert (
+            submission_result == job_name
+        ), f"Job submission failed, expected {job_name}, got {submission_result}"
         print(f"✅ Successfully submitted RayJob '{job_name}' against existing cluster")
 
         # Monitor the job status until completion
@@ -105,19 +113,19 @@ def assert_rayjob_submit_against_existing_cluster(self, cluster, accelerator, nu
     def monitor_rayjob_completion(self, rayjob: RayJob, timeout: int = 900):
         """
         Monitor a RayJob until it completes or fails.
-        
+
         Args:
             rayjob: The RayJob instance to monitor
             timeout: Maximum time to wait in seconds (default: 15 minutes)
         """
         print(f"⏳ Monitoring RayJob '{rayjob.name}' status...")
-        
+
         elapsed_time = 0
         check_interval = 10  # Check every 10 seconds
-        
+
         while elapsed_time < timeout:
             status, ready = rayjob.status(print_to_console=True)
-            
+
             # Check if job has completed (either successfully or failed)
             if status == CodeflareRayJobStatus.COMPLETE:
                 print(f"✅ RayJob '{rayjob.name}' completed successfully!")
@@ -128,11 +136,11 @@ def monitor_rayjob_completion(self, rayjob: RayJob, timeout: int = 900):
                 print(f"🏃 RayJob '{rayjob.name}' is still running...")
             elif status == CodeflareRayJobStatus.UNKNOWN:
                 print(f"❓ RayJob '{rayjob.name}' status is unknown")
-            
+
             # Wait before next check
             sleep(check_interval)
             elapsed_time += check_interval
-        
+
         # If we reach here, the job has timed out
         final_status, _ = rayjob.status(print_to_console=True)
         raise TimeoutError(

tests/e2e/rayjob_existing_cluster_oauth_test.py

@@ -13,6 +13,7 @@
 
 # This test creates a Ray Cluster and then submits a RayJob against the existing cluster on OpenShift
 
+
 @pytest.mark.openshift
 class TestRayJobExistingClusterOauth:
     def setup_method(self):
@@ -66,7 +67,7 @@ def run_rayjob_against_existing_cluster_oauth(self):
         print(f"✅ Ray cluster '{cluster_name}' is ready")
 
         job_name = "existing-cluster-rayjob"
-        
+
         rayjob = RayJob(
             job_name=job_name,
             cluster_name=cluster_name,
@@ -80,9 +81,13 @@ def run_rayjob_against_existing_cluster_oauth(self):
         )
 
         # Submit the job
-        print(f"🚀 Submitting RayJob '{job_name}' against existing cluster '{cluster_name}'")
+        print(
+            f"🚀 Submitting RayJob '{job_name}' against existing cluster '{cluster_name}'"
+        )
         submission_result = rayjob.submit()
-        assert submission_result == job_name, f"Job submission failed, expected {job_name}, got {submission_result}"
+        assert (
+            submission_result == job_name
+        ), f"Job submission failed, expected {job_name}, got {submission_result}"
         print(f"✅ Successfully submitted RayJob '{job_name}'")
 
         # Monitor the job status until completion
@@ -95,19 +100,19 @@ def run_rayjob_against_existing_cluster_oauth(self):
     def monitor_rayjob_completion(self, rayjob: RayJob, timeout: int = 300):
         """
         Monitor a RayJob until it completes or fails.
-        
+
         Args:
             rayjob: The RayJob instance to monitor
             timeout: Maximum time to wait in seconds (default: 15 minutes)
         """
         print(f"⏳ Monitoring RayJob '{rayjob.name}' status...")
-        
+
         elapsed_time = 0
         check_interval = 10  # Check every 10 seconds
-        
+
         while elapsed_time < timeout:
             status, ready = rayjob.status(print_to_console=True)
-            
+
             # Check if job has completed (either successfully or failed)
             if status == CodeflareRayJobStatus.COMPLETE:
                 print(f"✅ RayJob '{rayjob.name}' completed successfully!")
@@ -118,11 +123,11 @@ def monitor_rayjob_completion(self, rayjob: RayJob, timeout: int = 300):
                 print(f"🏃 RayJob '{rayjob.name}' is still running...")
             elif status == CodeflareRayJobStatus.UNKNOWN:
                 print(f"❓ RayJob '{rayjob.name}' status is unknown")
-            
+
             # Wait before next check
             sleep(check_interval)
             elapsed_time += check_interval
-        
+
         # If we reach here, the job has timed out
         final_status, _ = rayjob.status(print_to_console=True)
         raise TimeoutError(