UUIDs in 10 Languages — Part 6: Clojure, Haskell, and R

We’ve reached the final part of our language journey. This time, we explore UUID generation and usage in:

Clojure: a Lisp for the JVM
Haskell: the purest of functional languages
R: the statistical powerhouse

Each of these environments treats UUIDs differently — but all with intention and elegance.

🌱 Clojure: UUIDs in a Lisp World

Because Clojure runs on the JVM, it gets easy access to Java’s built-in java.util.UUID.

🔧 Generate a UUID

clojure

(java.util.UUID/randomUUID)

You can wrap it in a utility function for reuse:

clojure

(defn gen-uuid [] (str (java.util.UUID/randomUUID)))

✅ Parse a UUID string

clojure

(java.util.UUID/fromString "550e8400-e29b-41d4-a716-446655440000")

🧠 Best Practices

Store UUIDs as strings when interacting with JSON or databases
Leverage clojure.spec or malli to validate UUID format
Convert UUIDs to strings early when returning in APIs

🧠 Haskell: UUIDs in Pure Functional Style

In Haskell, use the uuid and random packages to work with UUIDs.

🔧 Install

Add to your .cabal file or use Stack:

bash

cabal install uuid random

📦 Generate a UUIDv4

haskell

import Data.UUID.V4 (nextRandom)

main :: IO ()
main = do
  uuid <- nextRandom
  putStrLn $ "UUIDv4: " ++ show uuid

📥 Parse and Validate

haskell

import Data.UUID (fromString)

maybeUUID = fromString "550e8400-e29b-41d4-a716-446655440000"

🧠 Best Practices

Wrap UUIDs in newtypes for type safety in domain logic
Use UUIDs as keys in typed data stores (e.g. SQLite with persistent)
Leverage QuickCheck to test UUID generation and equality

📊 R: UUIDs in a Data Science Context

R supports UUIDs via the uuid package — widely used in data pipelines, reproducibility, and report generation.

🔧 Install

install.packages("uuid")

📦 Generate UUIDs

library(uuid)

UUIDgenerate() # returns a UUIDv4 string

You can generate multiple at once:

replicate(5, UUIDgenerate())

📊 Use Cases

Create unique row identifiers in data frames
Tag output files or reports
Track metadata in reproducible pipelines

✅ Store UUIDs in Data Frames

df <- data.frame(id = UUIDgenerate(n = 10), value = rnorm(10))

🧠 Best Practices

Keep UUIDs as strings for portability
Use set.seed() only if reproducibility is more important than uniqueness
Consider digest() for shorter hash-based IDs if UUIDv4 feels overkill

📘 Summary Table

Language	Generate	Parse/Validate	Notes
Clojure	`UUID/randomUUID`	`UUID/fromString`	JVM-native, idiomatic in Clojure
Haskell	`nextRandom`	`fromString`	Pure functional, strong typing
R	`UUIDgenerate()`	Not strict (string match)	Lightweight, great for data science

Final Thoughts

From the parentheses of Clojure to the purity of Haskell to the statistical flair of R — UUIDs show up everywhere. The key is understanding how each environment handles them, and how you can build reliable, readable, and reproducible systems around them.

🎉 That wraps our six-part series on UUIDs in 10 Languages!

Thanks for following along — and may your identifiers always be unique, immutable, and bug-free.

"UUIDs in 10 Languages" Part 6: Clojure, Haskell, and R