You don't need to leave #Java behind to gain modern language features. #Kotlin #Scala #Groovy, & others run on the same reliable #JVM & open new dev possibilities.

🛠 Choose the right tool for the job with Mihaela Gheorghe-Roman: https://javapro.io/2025/10/09/the-rise-of-jvm-languages-kotlin-scala-groovy-and-more/

#Jython @IntelliJScala

Which JVM language fits your stack? #Kotlin for Android, #Scala for Spark, #Groovy for testing, #Clojure for concurrency, #JRuby & #Jython for scripts. Each solves different dev pains—fully JVM-compatible.

Mihaela Gheorghe-Roman shows the big picture: https://javapro.io/2025/10/09/the-rise-of-jvm-languages-kotlin-scala-groovy-and-more/

Still writing Java 8 code? You may be missing out. Modern JVM languages bring you:

✔ Null-safety, Functional programming, Concise DSLs, Faster onboarding

Mihaela Gheorghe-Roman maps the evolving #JVM landscape: https://javapro.io/2025/10/09/the-rise-of-jvm-languages-kotlin-scala-groovy-and-more/

#Kotlin #Scala #Jython @IntelliJScala

Thanks to Werner Fouché's initiative, there is now a @jbangdev catalog for Jython!
As a result, running Jython scripts becomes even easier:

jbang run jython-cli@jython <jython-script>.py

or after install: jython-cli <jython-script>.py

https://github.com/jython/jbang-catalog

#java #jython #jbang #jdk

Ein lang ersehnter Wunsch von mir: Eigene #Clustering Methoden in #OpenRefine benutzen.

Verfügbar seit Version 3.9.0 und funktioniert seit 3.9.3 auch mit #Jython und #Clojure.

Hier eine Anleitung zur Benutzung im #FDMLab Blog.

https://fdmlab.landesarchiv-bw.de/workshop/openrefine-fortgeschrittene/19-erweitertes-clustering/

#LandesarchivBW

Imagine:
- small custom tool in #Python2 / #Jython, bundled to an .exe
- Last time bundled was a few years back
- executable used on CI server

Then:
- suddenly all builds across the Server fail 😳
- The CI server and your own PC fail executing your small tool, saying "This application needs #Java 8" 🤔
- But your CI Server and own PC _have_ Java 8 installed 🤨
- The fellas around you have seemingly the same tools installed and can execute the tool 🧐

#programming #magic #CI

True as always that the way to make software run faster is to make it do less operations. After all, CPUs can only execute a fixed number of operations per unit of time.

Here, I tweaked code for serial section registration that drops execution time from 27 seconds to 100 milliseconds: a 270x speed up.

All it had to do is to search for matching SIFT features in one image only within a predetermined radius centered on one SIFT feature in another image. Extremely effective for when e.g., the maximum translation is known.

The matching code using a KDTree:
https://github.com/acardona/scripts/blob/master/java/asm/my/PointMatchesFast.java#L56

The test script:
https://github.com/acardona/scripts/blob/dev/python/imagej/FIBSEM/tests/test_matchNearbyFeatures.py

#FijiSc #java #jython #volumeEM #vEM