Taragolis commented on PR #28248:
URL: https://github.com/apache/airflow/pull/28248#issuecomment-1344013229
Just a thought:
- Do we actually need run this in the loop?
- Could we actually run by use the same objects and use `flaky` library
(which actually install as dev dependency) for multiple execution?
- Because each flaky run it is separate test than we actually could decrease
`execution_timeout`
Some scratch implementation
```python
@pytest.mark.quarantined
@pytest.mark.setup_timeout(0)
class TestCeleryHang:
RUNS = 500
@classmethod
def setup_class(cls):
task = MockTask()
num_tasks = 26
cls.executor = celery_executor.CeleryExecutor()
cls.task_tuples_to_send = [(None, None, None, task) for _ in
range(num_tasks)]
cls.expected = [(None, None, 1) for _ in range(num_tasks)]
@pytest.mark.flaky(max_runs=RUNS, min_passes=RUNS)
@pytest.mark.execution_timeout(5)
def test_send_tasks_to_celery_hang(self, register_signals):
"""
Test that celery_executor does not hang after many runs.
"""
assert self.executor._send_tasks_to_celery(self.task_tuples_to_send)
== self.expected
```
WDYT?
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