Clojure Online Compiler - A REPL in Your Browser
Rich Hickey designed Clojure with a clear opinion: most bugs come from mutable state. So he built a Lisp that runs on the JVM where all data structures are immutable by default. Vectors, maps, sets, they're all persistent data structures. You don't change them. You create new versions.
The catch? Running Clojure locally means running the JVM. That's a multi-hundred-megabyte install, plus Leiningen or tools.deps, plus startup times that make you wait a few seconds every time you launch a REPL. For quick experiments, that friction adds up.
A Clojure online compiler gives you a REPL-like experience without any of that.
Data transformation, the Clojure way
Clojure's threading macros (-> and ->>) are what make data transformation readable. Instead of writing nested function calls from the inside out, you write them top to bottom.
Paste this into OneCompiler's Clojure editor:
(def people
[{:name "Alice" :age 32 :dept "engineering"}
{:name "Bob" :age 28 :dept "design"}
{:name "Charlie" :age 45 :dept "engineering"}
{:name "Diana" :age 37 :dept "engineering"}
{:name "Eve" :age 24 :dept "design"}])
;; Find average age per department
(let [by-dept (->> people
(group-by :dept)
(map (fn [[dept members]]
[dept
(double (/ (reduce + (map :age members))
(count members)))]))
(into (sorted-map)))]
(doseq [[dept avg-age] by-dept]
(println (str dept ": " avg-age " avg age"))))
;; Filter and transform
(println "\nEngineers over 30:")
(->> people
(filter #(= (:dept %) "engineering"))
(filter #(> (:age %) 30))
(map :name)
(clojure.string/join ", ")
println)
That ->> macro threads the result of each expression as the last argument to the next function. It reads naturally: take people, filter them, extract names, join them. No intermediate variables. No mutation.
Why Clojure clicks in a browser
Clojure developers love the REPL. The whole workflow is built around evaluating expressions interactively and building up solutions piece by piece. An online compiler fits this perfectly. You write an expression, run it, see the result, adjust. The feedback loop is tight.
The JVM startup penalty doesn't apply in a browser environment since OneCompiler keeps the runtime warm. You get output in seconds, not after staring at a loading JVM.
Immutable by default, and why that matters
Here's the thing about Clojure that takes a while to appreciate. When you call assoc on a map, you get a new map. The old one is untouched. When you conj onto a vector, same thing. This means you can pass data around freely without worrying about something else modifying it.
It sounds limiting. In practice, it eliminates entire categories of bugs. And the persistent data structures under the hood share structure, so it's efficient too.
Using OneCompiler for Clojure
OneCompiler is straightforward for Clojure work:
- Write expressions and see results immediately
- Share your code via URL, useful for showing examples in Slack or forum posts
- No JVM install, no Leiningen, no project.clj
- Works on any device with a browser
Whether you're exploring Clojure for the first time or you just need to validate a reduce before putting it in production, it does the job.