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

Workshop - Erweitertes Clustering | FDMLab@LABW

Wir verwenden eigene Clustering Methoden in OpenRefine, um Schreibweisen zu vereinheitlichen.

FDMLab@LABW
We're happy to share that Werner Fouché has written a follow-up article about his Jython/JBang integration effort we shared last week. It provides example code to get you started, including a Spring rest client example.
https://medium.com/@werner.fouche/running-jython-scripts-with-jbang-part-2-d13b3699c015 #jython #jbang
Running Jython scripts with JBang using PEP 723 (Part 2)

In the previous article about using JBang to run Jython scripts we explained how to use a Java helper program with JBang to seamlessly resolve external Maven dependencies — see…

Medium
We're excited to share that there has been an effort by Werner Fouché to integrate Jython with JBang. Please checkout his Medium article to learn how you can run Jython scripts on JBang easily! https://medium.com/@werner.fouche/running-jython-scripts-with-jbang-using-a-java-helper-program-9ab9f8e35ddc #jython #jbang @jbangdev
Running Jython scripts with JBang using a Java helper program

Jython is an implementation of Python in Java, and has a multi-decade development history. It was one of the earliest scripting languages for the Java VM (JVM). Initially it was called JPython but…

Medium

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

scripts/java/asm/my/PointMatchesFast.java at master · acardona/scripts

A collection of scripts related to neural circuit analysis and image processing for python, Fiji, TrakEM2, CATMAID, and others. - acardona/scripts

GitHub

"Type annotations are unsupperted in Python 2"
😒😒

Will man Jython überhaupt noch verwenden? 🤐

#Jython #Python #Python2 #LegacyCode

Mh...in nem Jython Projekt, in dem im Python Code imports aus ner Java-Bibliothek stattfinden.....wie bring ich meinem IntelliJ bei, dass es die auflöst und nicht als fehlerhafte Imports anzeigt? 🧐

#Python #Java #Jython #IntelliJ

Announcing coatl-dev/actions v3.1.0.

Features:

- setup-jython: Set up a specific version of Jython and add the command-line tools to the PATH.

https://github.com/coatl-dev/actions/releases/tag/v3.1.0

#GitHub #jython #java #zulu #azul

Release v3.1.0 · coatl-dev/actions

What's Changed build(deps): pre-commit autoupdate by @pre-commit-ci in #50 feat: add setup-jython by @cesarcoatl in #51 Full Changelog: v3.0.1...v3.1.0

GitHub

I wonder how other #python implementations like #pypy and #jython would fare in this:

https://mastodon.social/@vruz/112145750607678621

I love Python, but 75 times C's energy consumption it's a lot.

Interesting that #Perl seems to fare worse?