I know this will be seen as a duplicate, but I have looked around before asking this question, however all of the questions seem to be either outdated or don't help at all with my problem. This is where I've looked before writing this question:
I'm currently working on a project that heavily uses Celery to handle asynchronous tasks; to make the entire code-base stable I'm writing unit tests for the entire project however I haven't been able to write a single working test for Celery so far.
Most of my code needs to keep track of the tasks that were run in order to determine wether or not all results are ready to be queried. This is implemented in my code as follows:
@app.task(bind=True)
def some_task(self, record_id):
associate(self.request.id, record_id) # Not the actual DB code, but you get the idea
# Somewhere else in my code, eg: Flask endpoint
record = some_db_record()
some_task.apply_async(args=[record.id])
Since I don't have a *nix based machine to run my code on, I tried solving this by setting the always eager option to true, however this causes issues whenever any sub-task tries to query the result:
@app.task(bind=True)
def foo(self):
task = bar.apply_async()
foo_poll.apply_async(args=[task.id])
@app.task(bind=True, max_retries=None):
def foo_poll(self, celery_id)
task = AsyncResult(celery_id)
if not task.ready(): # RuntimeError: Cannot retrieve result with task_always_eager enabled
return self.retry(countdown=5)
else:
pass # Do something with the result
@app.task
def bar():
time.sleep(10)
I tried fixing this by patching the AsyncResult
methods, however this caused issues as self.request.id
would be None
:
with patch.object(AsyncResult, "_get_task_meta", side_effect=lambda: {"status": SUCCESS, "result": None}) as method:
foo()
@app.task(bind=True)
def foo(self):
pass # self.request.id is now None, which I need to track sub-tasks
Does anyone know how I could do this? Or if Celery is even worth using anymore? I'm at the point where I find the documentation and any questions related to testing so overwhelmingly complex I just feel like ditching it all together and just go back to multithreading.
It is possible to test the function without the celery task binding by calling it directly and by using a mock to replace the task object.
The inner function is hidden behind some_task.__wrapped__.__func__
.
Here is an example of how to use it in a test case:
def test_some_task(self):
mock_task = Mock()
mock_task.request.id = 5 # your test data here
record_id = 5 # more test data
some_task_inner = some_task.__wrapped__.__func__
some_task_inner(mock_task, record_id)
# ...
I had about the same issue and came up with two possible approaches:
if self.request.called_directly
and run task directly if True or with apply_async
if False.task.ready()
and other statuses check with functions where I check for ALWAYS_EAGER
and task readiness. Eventually I came up with kinda mix of both with the rule to avoid nested tasks as much as I can. And also put as little code in @app.task
as I can in order to be able to test task functions in as much isolation as possible.
It might look quite frustrating and awful, but in fact it's not.
Also you can check how big guys like Sentry do this (spoiler: mocks and some nifty helpers).
So it's definitely possible, it's just not an easy way to find some best practices around.
I haven't used celery for some time, and unless things have changed you should be able to call your methods directly to exercise them as unit tests.
@app.task(bind=True, max_retries=None):
def foo_poll(self, celery_id)
task = AsyncResult(celery_id)
if not task.ready(): # RuntimeError: Cannot retrieve result with task_always_eager enabled
return self.retry(countdown=5)
else:
pass # Do something with the result
For your unit test you could:
AsyncResult
, to trigger the correct branchretry
method and assert it's calledThis, of course, only exercises your method's logic, and not celery. I usually put one or two integration (collaboration) test that specify ALWAYS_EAGER so that it goes through the celery code, even though the celery will be executed in memory without a queue.
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