This is just a long way of asking: "How does sync_to_async work with blocking IO, and gevent/psycogreen"?
For example:
from myapp.models import SomeModel
from asgiref.sync import sync_to_async
from gevent.threadpool import ThreadPoolExecutor as GThreadPoolExecutor
conf = {
"thread_sensitive": False,
"executor": GThreadPoolExecutor(max_workers=1)
}
await sync_to_async(SomeModel.objects.all, **conf)()
The third kwarg that can be passed to asgiref's sync_to_async
is an executor
the executor is a type of concurrent.futures.ThreadPoolExecutor
According to the documentation gevent.threadpool.ThreadPoolExecutor
more or less inherits and wraps concurrent.futures.ThreadPoolExecutor
Say for example I want to use a werkzeug
DispatcherMiddleware
, and wrap an ASGI app.
Think FastAPI mounted to the inside of an older monolithic django WSGI app ( using eventlet / gevent / psycogreen / monkey patching )
Here's my attempt at doing it.
Basically, how to get django async-ish ORM?
try:
from gevent.threadpool import ThreadPoolExecutor as GThreadPoolExecutor
from django.conf import settings
if settings.GEVENT_DJANGO_ASYNC_ORM:
from gevent import monkey
monkey.patch_all()
def monkey_patch_the_monkey_patchers(ex):
from .patch_gevent import _FutureProxy
def submit(ex, fn, *args, **kwargs): # pylint:disable=arguments-differ
print(fn, *args, **kwargs)
with ex._shutdown_lock: # pylint:disable=not-context-manager
if ex._shutdown:
raise RuntimeError('cannot schedule new futures after shutdown')
future = ex._threadpool.spawn(fn, *args, **kwargs)
proxy_future = _FutureProxy(future)
proxy_future.__class__ = concurrent.futures.Future
return proxy_future
ex.submit = submit
return ex
MonkeyPoolExecutor = monkey_patch_the_monkey_patchers(GThreadPoolExecutor)
conf = {"thread_sensitive": False, "executor": MonkeyPoolExecutor(max_workers=1)}
executor_ = MonkeyPoolExecutor
except Exception as e:
print(e)
print('defaulting django_async_orm')
pass
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