If you're doing any kind of database / external network calls - won't you gain a huge amount of requests per second?
I ask partly because on one of my projects, we have a fastapi app, but it's not using async, and I have been toying with the idea of converting it to async. It will take some work though because it uses libs that don't support async.
I thought the advantages would be worth it because we hit postgres and/or redis on all requests.
Any other use-case you are better off going with the simplicity of a sync framework like Flask. For databases you are way worse with async, see why from the Python database god himself: https://techspot.zzzeek.org/2015/02/15/asynchronous-python-a...
Not sure what libs you use, you'll probably need to switch libraries, it's not common for one lib to support both sync/async. I'm using aiohttp for http/websockets and asyncpg for postgres, running on uvloop as the base event loop.
Something which is trivial with asyncio: I receive 10 consecutive heavy websockets requests, I spawn a task to handle each one of them and they will be served back out of order as Postgres returns results. With no locking or messing with threads.
Another benefit is knowing for certain your code won't be interrupted unless you call "await", this simplifies a lot using shared state without requiring locks.
Only if they can be parallelized. I'm not sure if I would choose Flask if I had such a complex application.