RYryadh·Nov 14, 2023Submission
ClickPy: Real-Time Analytics on PyPI Package Downloads
3 points · Open discussionClickHouse
clickpy
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ClickHouse / clickpy
clickpy
PyPI analytics powered by ClickHouse
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158GitHub stars
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PyPI analytics powered by ClickHouse
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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.
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Observed mentions: 2023-11-03 13:02:36 UTC to 2023-11-14 11:52:10 UTC.
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| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| Nov 3 | 2023-11-03 00:00:00 UTC | 2023-11-04 00:00:00 UTC | 1 | 1 | 0 |
| Nov 4 | 2023-11-04 00:00:00 UTC | 2023-11-05 00:00:00 UTC | 0 | 0 | 0 |
| Nov 5 | 2023-11-05 00:00:00 UTC | 2023-11-06 00:00:00 UTC | 0 | 0 | 0 |
| Nov 6 | 2023-11-06 00:00:00 UTC | 2023-11-07 00:00:00 UTC | 0 | 0 | 0 |
| Nov 7 | 2023-11-07 00:00:00 UTC | 2023-11-08 00:00:00 UTC | 0 | 0 | 0 |
| Nov 8 | 2023-11-08 00:00:00 UTC | 2023-11-09 00:00:00 UTC | 0 | 0 | 0 |
| Nov 9 | 2023-11-09 00:00:00 UTC | 2023-11-10 00:00:00 UTC | 0 | 0 | 0 |
| Nov 10 | 2023-11-10 00:00:00 UTC | 2023-11-11 00:00:00 UTC | 0 | 0 | 0 |
| Nov 11 | 2023-11-11 00:00:00 UTC | 2023-11-12 00:00:00 UTC | 0 | 0 | 0 |
| Nov 12 | 2023-11-12 00:00:00 UTC | 2023-11-13 00:00:00 UTC | 0 | 0 | 0 |
| Nov 13 | 2023-11-13 00:00:00 UTC | 2023-11-14 00:00:00 UTC | 0 | 0 | 0 |
| Nov 14 | 2023-11-14 00:00:00 UTC | 2023-11-15 00:00:00 UTC | 1 | 1 | 0 |
What Hacker News says
2 sourcesShow HN: ClickPy – OSS project and service for Python analytics using ClickHouse
Thought i'd share some recent work i'd done after being generally frustrated as to the available analytics for Python modules. Most seem to be either limited in time or incur charges to query.
Code is Apache 2 at https://github.com/clickHouse/clickpy
The downloads for Python modules are actually available in BigQuery - a row for every package download in the world. Last time i checked it's the largest BigQuery public dataset at almost 700b rows. Wanting to do some serious analytics led to a few frustrations though:
- speed for queries - BigQuery is great for complex SQL, less so for fast analytics.
- cost :) especially as i wanted to offer this for free.
Knowing that ClickHouse excels at this sort of problem (as a ClickHouse employee full disclosure), I set about exporting the data to GCS and importing to ClickHouse. A weekend learning Ne
Read the rest
xtJS+React and some help from a designer friend (thanks Daniel!) and ClickPy was born!
For now the analytics are quite simple but I plan to enrich them over time. I've made the cluster also public and read-only so users can run the app themselves - and hopefully contribute back.
Finally, i'm planning to keep the dataset up-to-date daily (maybe more in the future). It's proven a useful test case for the ClickHouse dev team and has already found a few issues in the core db.
Contributions welcome and let me know if you find it useful for digging into the downloads of your own package.
Cheers,
GingerWizard