asyncpg VS psycopg2

asyncpg: this was the gold standard async database driver for Postgres, being one of the first to market and most performant. While all other drivers use the C library libpq to interface with Postgres, MagicStack opted to rewrite their own custom implementation and also deviate from Python DBAPI spec. If performance is your main criteria here, then asyncpg is probably the best option.

If you are operating in an environment with asyncio check out asyncpg - https://github.com/MagicStack/asyncpg

Performance charts speak for themselves. This lib uses the binary protocol while most are using text based comms.

- 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).

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.

# Palindrome project Project used to explain my view on a django project architecture, explained on my [series of posts](https://dev.to/pcampos119104/django-project-setup-part-1-2e7a) ## Tools, libs, etc. Some time related files. Versions on Poetry. - [Python](https://www.python.org/) Programming languange - [django-environ](https://django-environ.readthedocs.io) Manage .envs in Django - [Poetry](https://python-poetry.org/) Python packaging and dependency management - poetry.lock - pyproject.toml - [Django](https://www.djangoproject.com/) Web framework written in Python - [Docker](https://www.docker.com/) Manage containers for dev environment - compose.yaml - compose/dev/Dockerfile - compose/dev/start - .env - [Just](https://just.systems/) encapsulate commands for easier use - justfile - [psycopg](https://www.psycopg.org/) Python adapter for Postgres # <-- new line ## Dev environment setup 1. Install Just, Docker and Poetry(opcional). 2. Copie .env.example to .env, no need for edtion. 3. `$ just build` ## Run the server for development 1. Certified that docker is up and running 2. `$ just runserver` You can access on http://0.0.0.0:8000/

You can practice both by using https://www.psycopg.org from your Python code to communicate with your database. When I wanted to practice some SQL, that's what I did (we use psycopg at work, so that's what I practiced with, making a dream journal thingy for myself that was better than just noting stuff in a notepad because I could then look up e.g. what other stuff was correlated with Y, how many times I dreamed of X, etc. etc.)

But seems like it should work with Django 3, which you have specified https://github.com/psycopg/psycopg2/issues/1293

If you're using Postgres for your SQL, look at the "copy' method of the psycopg module (see https://www.psycopg.org/articles/2020/11/15/psycopg3-copy/) . It's much faster than INSERTs in my experience (YMMV).

Back when I used Psycopg2, there was no -binary package, so you'd get libpq set up similarly to pg-native. Docs say:

> The binary package is a practical choice for development and testing but in production it is advised to use the package built from sources.

Relevant GitHub discussion: https://github.com/psycopg/psycopg2/issues/674

I dunno, this seems worse to me.

Just go to the more easily readable docs here. I’m sorry, but the linked article is terrible.

psycopg2-binary. See https://github.com/psycopg/psycopg2/issues/1286.

psycopg2-binary, PostgreSQL Database adapter for python.

... # psycopg2==2.9.3 # https://github.com/psycopg/psycopg2 ...

I sometimes do this in testing. For example, consider the library used to communicate with a Postgres database, psycopg.