It means that the task is taking longer than one second and by default only one concurrent execution is allowed for a given job. I cannot tell you how to handle this without knowing what the task is about.
(1) You can use the app.app_context() context manager to set the application context. I imagine usage would go something like this: from apscheduler.scheduler import Scheduler def checkSecondApi(): with app.app_context(): # Do whatever you were doing to check the second API @app.before_first_request def initialize(): apsched = Scheduler() apsched.start() apsched.add_interval_job(checkFirstAPI, seconds=5) apsched.add_interval_job(checkSecondAPI, seconds=5) apsched.add_interval_job(checkThirdAPI, seconds=5) Alternatively, you … Read more
Because Gunicorn is starting with 8 workers (in your example), this forks the app 8 times into 8 processes. These 8 processes are forked from the Master process, which monitors each of their status & has the ability to add/remove workers. Each process gets a copy of your APScheduler object, which initially is an exact … Read more
In debug mode, Flask’s reloader will load the flask app twice (How to stop Flask from initialising twice in Debug Mode?). I’m not sure why this is, but it causes apscheduler’s jobs to be scheduled twice. A quick print “loaded scheduler” right before sched.start() confirms this. There are a couple ways around this, as mentioned … Read more
In your def demo_async(urls), try to replace: loop = asyncio.get_event_loop() with: loop = asyncio.new_event_loop() asyncio.set_event_loop(loop)