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A new Calva is out calva The main new feature is ClojureDocs integration. • ClojureDocs examples in the hover-lookup of symbols. So that you can at a glance see neat ways and caveats about Clojure core-ish symbols. Each example have two buttons/links: ◦ To Rich Comment, prints the example to a rich comment below the top level form you are editing/viewing ◦ To Output Window, prints the example to the REPL/Output window • A command for printing all clojuredocs examples for the symbol under the cusror to a Rich Comment, default bound to `ctrl+alt+r d` (to go well with the command for opening a new rich comment block). • A command for printing all clojuredocs examples for the symbol under the cursor to the Output/REPL window, `ctrl+alt+o d` When the next clojure-lsp is released, this will be available in ClojureScript as well.. See to learn more. An early dev version of the hover is demoed in this tweet:

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This is fantastic, this is the pretty much the only featured I missed from Cursive 🙂 And the to rich comment / output window makes it even better than what cursive had.

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Very cool stuff

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awesome work!

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This is great and I so so like Rich comments highlight! How does "Go to Rich Comments" work in case of multiple ones?

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Hmm, sounds like I have created a Ux issue 😃 The command prints the example to a new Rich Comment.


There is a Go To Rich Comment in Calva, actually. Though it is not named like that (yet). It is named Create Rich Comment, which will create a new rich comment in “a good place”, which is most often below the current top level form. If there already is a rich comment there, then the command will go there.


And the new clojure-lsp is out! If you are using ClojureScript, then reload the VS Code window and you will get those ClojureDocs hovers. 🎉

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clojure-lsp New with lots of improvements and new features! 🎉 Check it out one of them, the live rename of locals For more information, come to #lsp

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Carsten Behring23:11:50

Aa new release of , the idiomatic machine learning library for Clojure, is out. Version 0.1.1 adds support for unsupervised learning together with various unsupervised models (projections, clustering and manifold)

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