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nackjicholson
aiosql
Python2020–2024
nackjicholson / aiosql

aiosql

Simple SQL in Python

2Distinct people
4Mentions
0Explicit recommenders
1.4KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Simple SQL in Python

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:56:07 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year4 dated mentions

Observed mentions: 2020-08-12 11:06:44 UTC to 2024-06-02 18:37:24 UTC.

0122020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments20202021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments20222023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments2024

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC110
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC202
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC000
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC000
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC110

What Hacker News says

4 sources
Related to ORMs/queries/performance, I have found the following combination really good: * aiosql[0] to write raw SQL queries and having them available as python functions (discussed in [1]) * asyncpg[2] if you are using Postgres * Map asyncpg/aiosql results to Pydantic[3] models * FastAPI[4] Pydantic models become the "source of truth" inside the app, they are designed as a copy of the DB schema, then functions receive and return Pydantic models in most cases. This stack also makes me think better about my queries and the DB design. I try to make sure each endpoint makes only a couple of queries. Each query may have multiple CTEs, but it's still only a single round-trip. That also makes you think about what to prefetch or not, maybe I want to also get the data to return if the request is OK and avoid another query. [0] https://github.com
Read the rest
In 12 requests per second: A realistic look at Python web frameworks
I've been using FastAPI for some time, and now I'm using it as a full web framework (not just for REST APIs). I like writing SQL without ORMs, so the combination of aiosql[0] + FastAPI + Jinja2 works great. Add HTMX[1] and even interactive websites become easy. That's in fact the stack I am using to build https://drwn.io/ and I couldn't enjoy it more. Thanks Sebastián for creating it! [0] https://github.com/nackjicholson/aiosql [1] https://htmx.org/
In FastAPI framework, high perf, easy to learn, fast to code, ready for production

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