news
Programming Leftovers
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Sandor Dargo ☛ I helped to build GetCracked's Intermediate C++ Roadmap
A few months ago, Coding Jesus reached out to me about collaborating on content for GetCracked, his C++ learning platform. The pitch was simple: he was building an interactive roadmap for intermediate C++ developers and wanted someone to help with building the technical content — quiz questions, curated resources, explanations. That sounded like exactly the kind of work I enjoy, so I said yes.
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Perl / Raku
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Olaf Alders ☛ How I Spent My Perl Toolchain Summit v2025 (Leipzig)
The Perl Toolchain Summit (PTS) is an annual event, held in Europe, where work on improving the Perl toolchain takes place. I was fortunate to be able to attend PTS once again in 2025. We met in Leipzig, Germany. This was my 1st trip to Leipzig and my 10th PTS in total.
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Python
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Juha-Matti Santala ☛ Y is for YAGNI - Python A to Z
While I like writing code to solve my technical problems and fulfill my software needs, I don’t like writing unnecessary code. Writing something because you thought it could be useful is often — unless you learned something from it — wasteful in terms of time and effort and added complexity.
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Shell/Bash/Zsh/Ksh
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Aman Mittal ☛ Taking the terminal seriously in the age of AI coding agents
Here’s my current Ghostty configuration: [...]
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R / R-Script
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Rlang ☛ wbstats 1.2.0 is now on CRAN
Programmatic Access to Data and Statistics from the World Bank API
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Dirk Eddelbuettel ☛ Dirk Eddelbuettel: corels 0.0.6 on CRAN: Microfix
An updated version of the corels package is now on CRAN! The ‘Certifiably Optimal RulE ListS (Corels)’ learner provides interpretable decision rules with an optimality guarantee—a nice feature which sets it apart in machine learning.
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R Statistics and Programming ☛ Visual Representation of Complex Data Using R: The tm and wordcloud Packages: Part Two
In part one of this tutorial, I discussed the use of the tm and wordcloud packages to create a visual representation of the most frequently used words in the 2026 Presidential State of the Union Address. I also discussed the code needed to generate an initial analysis of the wordcloud with a list of the 15 most used words and their frequency. I also discussed code that calculated a matrix consisting of the relative strength of association among 10 most commonly used words and other words used in the address. In this tutorial I will present code to display two wordclouds, one containing frequently used words in the 2009 State of the Union Address, and one containing the frequently used words from the 2017 State of the Union Address. I will also show the R code necessary to produce a simple bar graph of the most frequently used words and the association matrix for each wordcloud.
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