alt Hacker NewsIt's a blessing and a curse that zero innovation has occurred in the Clojure space since 2016. Pretty sure the only big things has been clojure.spec becoming more mainstream and the introduction of deps.edn to supplant lein. altho I am still partial to lein.
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Clojure 1.9: Spec.
Clojure 1.10: datafy/nav + tap> which has spawned a whole new set of tooling for exploring data.
Clojure 1.11: portable math (clojure.math, which also works on ClojureScript).
Clojure 1.12: huge improvements in Java interop.
And, yes, the new CLI and deps.edn, and tools.build to support "builds as programs".
> zero innovation has occurred in the Clojure space since 2016.
Oh, really? Zero, eh?
clojure.spec, deps.edn, Babashka, nbb, tap>, requiring-resolve, add-libs, method values, interop improvements, Malli, Polylith, Portal, Clerk, hyperfiddle/electric, SCI, flowstorm ...
Maybe you should've started the sentence with "I stopped paying attention in 2016..."?
I know others already pointed out a ton of things, but having worked with Clojure in 2016 and doing active Clojure development for my startup now I feel like I have to chime in too.
In 2016, Clojure was not great for serious data science. That has changed substantially and not just via Java Interop.
- It now has cross ecosystem GPU support via blueberry libraries like neanderthal, which in benchmarking, outperform some serious Java libraries in this space.
- It has columnar indexed JIT optimized data science libraries via cnuernber and techascent part of the Clojure ecosystem. In benchmarking they've outperformed libraries like numpy.
- The ecosystem around data science is also better. The projects aren't siloed like they used to be. The ecosystem is making things interoperate.
- You can now use Python from Clojure via the lib-pythonclj bindings. In general, CFFI is a lot better, not just for Python.
- The linters are way better than they used to be. The REPL support too.
Clojure already had one of the best efficiency scores in terms of code written to what is accomplished, but now you also get REPL integration, and LLMs have been increasingly capable of leveraging that. There are things like yogthos mycelium experiments to take advantage of that with RLLM calls. So its innovating in interesting new ways too, like cutting bugs in LLM generated code.
It just doesn't feel true to me that innovation isn't occurring. Clojure really has this import antigravity feel to it; things other languages would have to do a new release for, are just libraries that you can grab and try out (or maybe that's the python)