I have a function, that does multiple queries on the same dataset and I want to ensure all the queries would see exactly the same data.
In terms of SQL, this means REPEATABLE READ isolation level for the databases that support it. I don't mind having higher level or even a complete lockdown if the database isn't capable.
As far as I see, this isn't the case. I.e. if I run something like this code in one Python shell:
with transaction.atomic():
for t in range(0, 60):
print("{0}: {1}".format(t, MyModel.objects.count()))
time.sleep(1)
As soon as I do MyModel.objects.create(...)
in another, the value seen by the running loop increase immediately. Which is exactly what I want to avoid. Further tests shows the behavior matches READ COMMITTED level, which is too lax for my tastes.
I'd also want to stress the point, I want stricter isolation level only for a single function, not for the whole project.
What are my best options to achieve this?
In my particular case, the only database I care of is PostgreSQL 9.3+, but I also want some compatibility with SQLite3 in which case even completely locking the whole database is okay with me. Yet, obviously, the more general the solution is, the more preferred it is.
You're right, default transaction isolation level in postgres is READ COMMITTED. You can easily change it in settings to test whether it would fit your needs: https://docs.djangoproject.com/en/1.8/ref/databases/#isolation-level
Also I doubt you will face some performance issues because postgres operates very efficiently while working with transactions. Even in SERIALIZABLE mode. Also mysql has REPEATABLE READ default isolation level and as we see it doesn't hurt performance too.
Anyway you can set isolation mode manually whenever you need like this: http://initd.org/psycopg/docs/extensions.html#isolation-level-constants
To set custom transaction isolation level you can try smth like:
Also I would suggest you to change default mode in settings first (if you can). Then if will fit your needs you can remove it and modify code in special places.