quart VS asyncpg

Sorry. It's not Quartz, it's just Quart https://pgjones.gitlab.io/quart/

If you're looking for an experience that's very similar to Flask you can use Quart which is inspired by Flask. Quart even has a guide about how to migrate from a Flask application to using Quart! Flask's own documentation for async views actually recommends using Quart in some cases due to the performance hit from using a new event loop per request.

Flask getting async support is a huge step for the asyncio web ecosystem in Python. I wonder how Flask's ASGI support will evolve in parallel with Quart[1] which bills itself as the ASGI version of Flask and is maintained by a member of the Pallets team. One of the maintainers of Werkzeug even recommended using Quart[2]

[1] https://pgjones.gitlab.io/quart/

[2] https://github.com/pallets/werkzeug/issues/1322#issuecomment...

What we get with the async part of this release - If you would like to run an async library or your own async code from a flask route you can do that now. This is super useful, where let's say we have some async code that fetches data from many sources concurrently, or call multiple a few ML prediction endpoints at the same time (as long as they don't time out) using httpx and respond with some sort of outcome, or finally try that cool new async-only database library. A current (v2) limitation is that the you can't make concurrent requests using just the current asyncio implementation (an alternative with Flask API and ASGI: Quart). Typically in production gunicorn or uwsgi + threads/processes/gevent-eventlet is used and this makes Flask behave asynchronously. More here and here if interested.

For people looking to do async stuff with Flask, there is also Quart! It’s essentially an async port of Flask, with all your favorite, familiar methods!

I agree with the transition issues, Quart has this awkward code to try and get around this.

Appreciate the feedback! I forgot to pimp my favorite web framework, Quart, but I can attest to Flask and even Django being great. I always looked down on Django as too big but then I used it for my current company and I realized I was totally wrong. Easy to pick up, lots of functionality if you want it, but it doesn't force it on you.

- SqlAlchemy/asyncpg => you can’t use it if you’re using PgBouncer (necessary most of the time with Postgres) in transaction mode? What?? https://github.com/MagicStack/asyncpg/issues/1058

OK I stand corrected, asyncpg has these two C files:

https://github.com/MagicStack/asyncpg/blob/master/asyncpg/pr...

https://github.com/MagicStack/asyncpg/blob/master/asyncpg/pr...

If you are interested here is a post by the psycopg author about psycopg2 and 3 and performance versus asyncpg.

https://www.varrazzo.com/blog/2020/05/19/a-trip-into-optimis...

This pure Python library claims quite fabulous performance: https://github.com/MagicStack/asyncpg

I believe it because that team have done lots of great stuff but I haven't used it, I just remembered thinking it was interesting the performance was so good. Not sure how related it is to running on the asyncio loop (or which loop they used for benchmarks).

what a great post, we have had a ton of issues with users using pgbouncer and it's not because things are "broken" per se, it's just the situation is very complicated, and pgbouncer's docs are also IMO in need of updating to be more detailed and in a few critical cases less misleading, specifically the prepared statements docs.

This blog post refers to this misleading nature at https://jpcamara.com/2023/04/12/pgbouncer-is-useful.html#pre... .

> PgBouncer says it doesn’t support prepared statements in either PREPARE or protocol-level format. What it actually doesn’t support are named prepared statements in any form.

That's also not really accurate. You can use a named prepared statement just fine in transaction mode. start a transaction (so you aren't in autocommit), use a named statement, works fine. you just can't use it again in another transaction, because it will be "gone" (more accurately, "unmoored" - might be in your session, might be in someone else's session). Making things worse, when the prepared statement is "unmoored", its name can then conflict with another client attempting to use the same name.

so to use named prepared statements, you can less ideally name them with random strings to avoid conflicts, or you can DEALLOCATE the prepared statement(s) you used at the end of your transaction. for our users that use asyncpg, we have them use a uuid for prepared statements to avoid these name conflicts (asyncpg added this feature for us here: https://github.com/MagicStack/asyncpg/issues/837). however, they can just as well use DEALLOCATE ALL, set this as their `server_reset_query`, and then so that happens in transaction mode, also set `server_reset_query_always`, so that it's called at the end of transactions. Where pgbouncer here IMO entirely misleadingly documents this as "This setting is for working around broken setups that run applications that use session features over a transaction-pooled PgBouncer." - which is why nobody uses it, because pgbouncer claims this is "broken". It's not any more broken than it is to switch out the PostgreSQL session underneath a connection that uses multiple transactions. Pgbouncer can do better here and make this clearer and more accommodating of real world database drivers.

asyncpg is another great driver if you're using asyncio and want maximum performance (although they also break with DBAPI, but the tradeoff may be worth it).

asyncpg: 5.5k starts, last commit recently, ~150 issues, some incompatibility, few open PRs, extensive README. Includes benchmark showing it's supposedly 3x faster than aiopg and psycopg2, psycopg3 is not mentioned in the benchmark.

Quart-DB uses asyncpg to manage the connections and buildpg to parse the named parameter bindings.

A major performance boost specifically on inserts with timescaledb was actually starting to use https://github.com/MagicStack/asyncpg.

Simple query runs long when DB schema contains thousands of tables #186