shahar1 commented on code in PR #68800:
URL: https://github.com/apache/airflow/pull/68800#discussion_r3508238818
##########
providers/cncf/kubernetes/tests/unit/cncf/kubernetes/executors/test_kubernetes_executor.py:
##########
@@ -2239,16 +2307,30 @@ def test_executor_with_team_name(self):
assert executor.team_name == "ml_team"
assert executor.kube_config is not None
+ @pytest.mark.skipif(
+ AirflowKubernetesScheduler is None, reason="kubernetes python package
is not installed"
+ )
@pytest.mark.skipif(not AIRFLOW_V_3_2_PLUS, reason="Multi-team requires
Airflow 3.2+")
- def test_multiple_team_executors_isolation(self, monkeypatch):
+
@mock.patch("airflow.providers.cncf.kubernetes.kube_client.get_kube_client")
+
@mock.patch("airflow.providers.cncf.kubernetes.executors.kubernetes_executor_utils.client")
+
@mock.patch("airflow.providers.cncf.kubernetes.executors.kubernetes_executor_utils.KubernetesJobWatcher")
+ def test_multiple_team_executors_isolation(
+ self, mock_watcher, mock_client, mock_kube_client, monkeypatch
+ ):
"""Test that multiple team executors can coexist with isolated
resources."""
monkeypatch.setenv("AIRFLOW__TEAM_A___KUBERNETES_EXECUTOR__WORKER_PODS_CREATION_BATCH_SIZE",
"4")
monkeypatch.setenv("AIRFLOW__TEAM_B___KUBERNETES_EXECUTOR__WORKER_PODS_CREATION_BATCH_SIZE",
"8")
team_a_executor = KubernetesExecutor(team_name="team_a")
team_b_executor = KubernetesExecutor(team_name="team_b")
+ team_a_executor.job_id = 1
+ team_b_executor.job_id = 2
try:
+ # Queues are created lazily in start(), so each team executor gets
its own.
Review Comment:
Same comment as above :)
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