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sivers
srs
PLpgSQL2024–2025
sivers / srs

srs

Spaced Repetition in PostgreSQL functions

2Distinct people
2Mentions
0Explicit recommenders
60GitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Spaced Repetition in PostgreSQL functions

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 week2 dated mentions

Observed mentions: 2024-09-25 22:54:55 UTC to 2025-02-14 12:08:58 UTC. Weeks start Monday, UTC.

012024-09-23 00:00:00 UTC to 2024-09-30 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsSep 232024-09-30 00:00:00 UTC to 2024-10-07 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-10-07 00:00:00 UTC to 2024-10-14 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-10-14 00:00:00 UTC to 2024-10-21 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-10-21 00:00:00 UTC to 2024-10-28 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-10-28 00:00:00 UTC to 2024-11-04 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-11-04 00:00:00 UTC to 2024-11-11 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-11-11 00:00:00 UTC to 2024-11-18 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-11-18 00:00:00 UTC to 2024-11-25 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-11-25 00:00:00 UTC to 2024-12-02 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-12-02 00:00:00 UTC to 2024-12-09 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsDec 22024-12-09 00:00:00 UTC to 2024-12-16 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-12-16 00:00:00 UTC to 2024-12-23 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-12-23 00:00:00 UTC to 2024-12-30 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-12-30 00:00:00 UTC to 2025-01-06 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-01-06 00:00:00 UTC to 2025-01-13 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-01-13 00:00:00 UTC to 2025-01-20 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-01-20 00:00:00 UTC to 2025-01-27 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-01-27 00:00:00 UTC to 2025-02-03 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-02-03 00:00:00 UTC to 2025-02-10 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-02-10 00:00:00 UTC to 2025-02-17 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 commentsFeb 10

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
Sep 232024-09-23 00:00:00 UTC2024-09-30 00:00:00 UTC101
Sep 302024-09-30 00:00:00 UTC2024-10-07 00:00:00 UTC000
Oct 72024-10-07 00:00:00 UTC2024-10-14 00:00:00 UTC000
Oct 142024-10-14 00:00:00 UTC2024-10-21 00:00:00 UTC000
Oct 212024-10-21 00:00:00 UTC2024-10-28 00:00:00 UTC000
Oct 282024-10-28 00:00:00 UTC2024-11-04 00:00:00 UTC000
Nov 42024-11-04 00:00:00 UTC2024-11-11 00:00:00 UTC000
Nov 112024-11-11 00:00:00 UTC2024-11-18 00:00:00 UTC000
Nov 182024-11-18 00:00:00 UTC2024-11-25 00:00:00 UTC000
Nov 252024-11-25 00:00:00 UTC2024-12-02 00:00:00 UTC000
Dec 22024-12-02 00:00:00 UTC2024-12-09 00:00:00 UTC000
Dec 92024-12-09 00:00:00 UTC2024-12-16 00:00:00 UTC000
Dec 162024-12-16 00:00:00 UTC2024-12-23 00:00:00 UTC000
Dec 232024-12-23 00:00:00 UTC2024-12-30 00:00:00 UTC000
Dec 302024-12-30 00:00:00 UTC2025-01-06 00:00:00 UTC000
Jan 62025-01-06 00:00:00 UTC2025-01-13 00:00:00 UTC000
Jan 132025-01-13 00:00:00 UTC2025-01-20 00:00:00 UTC000
Jan 202025-01-20 00:00:00 UTC2025-01-27 00:00:00 UTC000
Jan 272025-01-27 00:00:00 UTC2025-02-03 00:00:00 UTC000
Feb 32025-02-03 00:00:00 UTC2025-02-10 00:00:00 UTC000
Feb 102025-02-10 00:00:00 UTC2025-02-17 00:00:00 UTC110

What Hacker News says

2 sources
sebnun·Feb 14, 2025Submission

Show HN: A New Way to Learn Languages

Hi HN, I’m Pablo, I built this application to learn languages using podcasts: https://www.langturbo.com (No signup required) There are a lot of tools to learn languages, but most of them focus on beginners (understandably so, that’s where the money is) but not many exist that target intermediate or advanced learners. The ones that exist make you find content on your own and then import that into their apps, which can be tricky when you don’t know where to look. LangTurbo has a unique curated database of podcasts by language (some even have dialect labels) that you can browse by topic, or search by keyword, so you can discover content and learn in the same place. Having a good language learning method is important, but having the motivation to keep learning is much more important. Some tools like Duolingo try to keep you motivated with “ga
Read the rest
mification”. I don’t like that, I think it gives you a false sense of accomplishment without real improvement. The way LangTurbo tries to keep you coming back is via the content itself. My goal is that you discover some podcast that interests you enough to keep coming back to listen to new episodes, the same way you listen to podcasts in your native language. I wrote more about the method here [1] The app also lets you learn without looking at the screen, you can listen to a podcast in the background and for each sentence you will first hear the translation in English and the native speaker after. I call it “poor man's Pimsleur mode”. Some things I learned while building the app: * Currently the best SRS algorithm is FSRS, the app uses this algorithm implemented in SQL (thanks to [2]) * Working with Expo (React Native) was a great experience, the app has web, iOS and Android (coming soon) clients sharing most of the codebase. * A lot of non-English podcasts have a feed with English as the language. I had to build a “probe” to get the correct language of a podcast, based on the text and audio of the feed. * Podcasts use “Dynamic Ad Insertion”, that means the content of the audio can change according to the request IP or the time of the request. * Still amazed by all the things Postgres can do Let me know what you think, happy to answer any questions. [1] https://www.langturbo.com/blog/langturbo/getting-started [2] https://github.com/sivers/srs
67 points · Open discussion

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