asyncpg
psycopg2
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asyncpg | psycopg2 | |
---|---|---|
15 | 19 | |
6,609 | 3,209 | |
1.5% | 1.7% | |
7.2 | 6.8 | |
13 days ago | about 15 hours ago | |
Python | C | |
Apache License 2.0 | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
asyncpg
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Ask HN: Is Python async/await some kind of joke?
- 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
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Differences from Psycopg2
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...
- Asyncpg – A Fast PostgreSQL Database Client Library for Python/Asyncio
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Ruby Outperforms C: Breaking the Catch-22
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).
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PgBouncer is useful, important, and fraught with peril
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.
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Library to connect Python to Postgresql
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).
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aiopg vs asyncpg vs psycopg3
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.
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Announcing Quart-DB
Quart-DB uses asyncpg to manage the connections and buildpg to parse the named parameter bindings.
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Should I use TimescaleDB or partitioning is enough?
A major performance boost specifically on inserts with timescaledb was actually starting to use https://github.com/MagicStack/asyncpg.
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Cascade of doom: JIT, and how a Postgres update led to 70% failure on a critical national service
Simple query runs long when DB schema contains thousands of tables #186
psycopg2
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Can I learn Python while practicing writing queries for SQL simultaneously? I've recently completed learning SQL and trying to get better at it.
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.)
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Installing psycopg2==2.8.6 throws an error
But seems like it should work with Django 3, which you have specified https://github.com/psycopg/psycopg2/issues/1293
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Uploading CSVs to a SQL table using Python
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).
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Underappreciated Challenges with Python Packaging
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.
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Integrate PostgreSQL Database In Python - A Hands-On Guide
Just go to the more easily readable docs here. I’m sorry, but the linked article is terrible.
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Has anyone made the switch from developing in Windows to macOS? Any general or specific advice about the switch?
psycopg2-binary. See https://github.com/psycopg/psycopg2/issues/1286.
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Dockerize a Django, React, and Postgres application with docker and docker-compose | by Anjal Bam
psycopg2-binary, PostgreSQL Database adapter for python.
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My Cookiecutter Django Setup
... # psycopg2==2.9.3 # https://github.com/psycopg/psycopg2 ...
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Why "import blescan as blescan"?
I sometimes do this in testing. For example, consider the library used to communicate with a Postgres database, psycopg.
- Engineers complaining about Docker for Mac?
What are some alternatives?
aiopg - aiopg is a library for accessing a PostgreSQL database from the asyncio
queries - PostgreSQL database access simplified
pymssql - Official home for the pymssql source code.
SQLAlchemy - The Database Toolkit for Python
awesome-mysql - A curated list of awesome MySQL software, libraries, tools and resources
PostgreSQL - Mirror of the official PostgreSQL GIT repository. Note that this is just a *mirror* - we don't work with pull requests on github. To contribute, please see https://wiki.postgresql.org/wiki/Submitting_a_Patch
pgbouncer - lightweight connection pooler for PostgreSQL
txpostgres - Twisted wrapper for asynchronous PostgreSQL connections
mysql-python - MySQLdb is a Python DB API-2.0 compliant library to interact with MySQL 3.23-5.1 (unofficial mirror)
psycopg - New generation PostgreSQL database adapter for the Python programming language
Python PG Extras - Python PostgreSQL database performance insights. Locks, index usage, buffer cache hit ratios, vacuum stats and more.