SSsschmitt·Aug 5, 2025
How is this different from https://github.com/nextjournal/clerk?
In Clojure Civitas – Publish Clojure Ideas and Explorationsnextjournal
clerk
Clojure2021–2025
nextjournal / clerk
clerk
⚡️ Moldable Live Programming for Clojure
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18Mentions
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2.1KGitHub stars
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⚡️ Moldable Live Programming for Clojure
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- babashka/babashka · linked in 2 of the same discussions
Mentioned in the same Hacker News threads. That is not proof they are substitutes.
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.
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HN mentions by year18 dated mentions
Observed mentions: 2021-11-04 14:10:42 UTC to 2025-08-05 16:22:29 UTC.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| 2021 | 2021-01-01 00:00:00 UTC | 2022-01-01 00:00:00 UTC | 2 | 1 | 1 |
| 2022 | 2022-01-01 00:00:00 UTC | 2023-01-01 00:00:00 UTC | 5 | 0 | 5 |
| 2023 | 2023-01-01 00:00:00 UTC | 2024-01-01 00:00:00 UTC | 7 | 1 | 6 |
| 2024 | 2024-01-01 00:00:00 UTC | 2025-01-01 00:00:00 UTC | 2 | 0 | 2 |
| 2025 | 2025-01-01 00:00:00 UTC | 2026-01-01 00:00:00 UTC | 2 | 0 | 2 |
What Hacker News says
18 sourcesIf you want this in Clojure, check out Clerk. [0]
As a bonus, you can continue to use whatever IDE you already use.
[0] https://github.com/nextjournal/clerk
In Show HN: Scripton – Python IDE with built-in realtime visualizationsClojure (either native JVM or Babashka)
Once you've got a repl up and running the JVM launch time isn't an issue and repl driven development lends itself well to data munging/exploration
Clojure's data centricity (functional, everything's a sequence, strong data manipulation std lib) really makes it a dream for these quick and dirty data transformation/exploration jobs
If you want to get fancy, https://github.com/nextjournal/clerk (notebook interface) and https://github.com/techascent/tech.ml.dataset (data frame library) will get you there
In Rust for the small things? but what about Python?Clojure's slow, deliberate development pace confuses people. The core team takes backwards compatibility very seriously. What you see with each new Clojure release is generally improved performance, better Java interop, and a smattering of new features. This is doubly true for 1.12 which is doing quite a bit of invisible work to make interop considerably better.
So what you don't see is a constant flux of "innovation" followed by a community having to adapt to those innovations. People pull Clojure examples out of books that are 12 or more years old and they still run.
I think there's some very exciting things in the Clojure space, such as Clerk (https://github.com/nextjournal/clerk) for live notebooks, and Babashka (https://github.com/borkdude/babashka) for amazing (and amazingly fast) scripting.
In Clojure 1.12.0 is now availableSome prior art: https://github.com/nextjournal/clerk
> Clerk notebooks always evaluate from top to bottom. Clerk builds a dependency graph of Clojure vars and only recomputes the needed changes to keep the feedback loop fast.
In XetCache: Improve Jupyter notebook reruns by caching cellsClojure's lazy sequences by default are wonderful ergonomically, but it provides many ways to use strict evaluation if you want to. They aren't really a hassle either. I've been doing Clojure for the last few years and have a few grievances, but overall it's the most coherent, well thought out language I've used and I can't recommend it enough.
There is the issue of startup time with the JVM, but you can also do AOT compilation now so that really isn't a problem. Here are some other cool projects to look at if you're interested:
Malli: https://github.com/metosin/malli
Babashka: https://github.com/babashka/babashka
Clerk: https://github.com/nextjournal/clerk
In Critique of Lazy Sequences in ClojureWe use a giant pile of Clojure (almost everything, with specific measured exceptions, is). As a side effect, we have a lot of data. Not necessarily a lot in the sense of "big S3 bill", but definitely a lot in the sense of "you might not expect this being in a machine-readable format".
Things like: what Lambdas existed in a customer AWS account 6 months ago in us-east-2 that had access to a specific SQS queue" (because we learned later that one of the consumers of that queue would actually consume Python pickles if you asked nicely, and hence get you RCE).
As a side effect, we do a lot of data diffing: just mostly on more vanilla Clojure structures rather than data sets in the Datasette/CSV/... sense.
For example, we have tooling (e.g. [recidiffist], which we also have wired up to Terraform + S3, so if you write some files to S3, you can g
Read the rest
et the structured diffs right next to it for free). It's one of those things that's simple and works ridiculously well. Well, if you do it consistently anyway. "Let's look at what resources aren't managed by IAC, and how that has changed historically" is an interesting question to me, but I couldn't do it without having that data available, encoded in a way that didn't pre-suppose how it would be used.
Even though we mean "explanation" differently, this really is critical for enabling explanation and exploration. While many of these pieces of data (e.g. "historical complete snapshots of AWS environments") aren't big compared to a lot of corporate data lakes or log management systems, they're way bigger than what fits in my tiny human brain at once. They're still amenable to fast local analysis. We use [clerk] for amazing notebooks to aid in that.
Where this all comes together is in the encoded, and machine-evaluatable, expressions. The way you do a Cloud audit is you write a Clojure program: you develop invariants about the environment that are or at least should be true, and then you talk about the places that didn't work out.
[recidiffist]: https://github.com/latacora/recidiffist
[clerk]: https://github.com/nextjournal/clerk
Checkout Clerk from the Clojure community [0]. Presumably it would be possible to extend a new language like Mojo (Python-superset) to support that kind of dev workflow to AI.
[0] https://github.com/nextjournal/clerk
In AI Workbooks – A notebook interface for LLMs, image and audio modelsMoldable Live Programming for Clojure
105 points · Open discussionI've been really enjoying using Clojure with Clerk: https://github.com/nextjournal/clerk
It's a bit like a Jupyter notebook, but you get to use your own editor, you still have a normal Clojure REPL, it's stored in git like "normal" code, etc.
For exploratory, information processing type work, it's pretty great.
Demo here: https://www.youtube.com/watch?v=3bs3QX92kYA
In Morse, an open-source interactive tool for inspecting ClojureTo name a few: https://github.com/xtdb/xtdb, https://github.com/nextjournal/clerk, https://github.com/penpot/penpot, https://github.com/metabase/metabase
In Clojure Turns 15 panel discussion video> The state of the in-memory image had gotten totally out of sync with the codebase.
I have not used it, but I heard that Clojure Clerk is supposed to help with this.
https://github.com/nextjournal/clerk
In The one about Lisp interactivityI was looking for a new data notebook toy to ease the tedium of reporting some metrics.
I found the clojure-based https://github.com/nextjournal/clerk which I like the look of and remember clojure being rather pleasing interactively.
That lisp and Julia might have some commonality made me look for something similar (that isn't jupyter) for Julia. Seems like https://github.com/fonsp/Pluto.jl is such a thing.
Does anyone have any experience of either they could share?
In From Common Lisp to JuliaThere’s a tool called Clerk which among other things resolves this concern about out of sync definitions https://github.com/nextjournal/clerk
In Clojure 15th Anniversary: A RetrospectiveSome interesting links from this talk:
Maria https://www.maria.cloud/
Glamorous Toolkit https://gtoolkit.com/
Data Rabbit https://datarabbit.com/
Nextjournal https://nextjournal.com/
Clerk https://github.com/nextjournal/clerk
Enso https://enso.org/
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