Free, Libre, and Open Source Software Leftovers

posted by Roy Schestowitz on Jun 05, 2026

• John D Cook ☛ Common patterns in Linux tools that go back to ed(1)

  Similarly, ed(1) is the Latin of Linux [1]. Many conventions in command line utilities follow conventions that go back to the ed(1) line editor. They may go back even further. Just as Latin didn’t come out of nowhere, neither did ed(1), but you can’t go back indefinitely. It’s convenient to start history somewhere, and this post will start with ed(1) just as much discussion of Western linguistics starts with Latin.

  The following are features of ed(1) that live on in sed, awk, grep, vi, perl, bash, etc.

• University of Toronto ☛ The Emacs packages that I use (as of June 2026)

  My Emacs configuration seems to have more or less settled down again after a flurry of changes, so it's time to update my previous list of Emacs packages that I use, so that I can come back to this entry later and see how things have changed over time. A bunch of things haven't changed since last time so I'm going to put the unchanged stuff at the bottom.

• University of Toronto ☛ My GNU Emacs completion setup (as of June 2026)

  In GNU Emacs, completion of things is a complex subject. There are at least two sorts of completion (in the minibuffer and in buffers you're editing) and many options for how things work. There's a whole ecology of third party packages for changing how both sorts of completion operate, some of which have become built in to GNU Emacs over time. For various reasons (cf) I'm going to write down my current setup for this.

• Lessons Learnt from Our BI Journey: From Open Source to SDV Products Development

  Luis Cañas Díaz and I shared lessons from our BI journey at the Eclipse Foundation SDV webinar — from open source to automotive. Methodology, real use cases, and hard-won lessons on data, metrics, and insights.

• Web Browsers/Web Servers/Feed Readers

  • Mihai Parparita ☛ persistent.info: How I consume Bluesky (and Twitter and Mastodon)

    tl;dr: I’ve added Sky Feeder and Tweeter Feeder to join my earlier Masto Feeder tool, allowing me (or anyone else who signs in) to follow accounts from all three social networks in a feed reader.

  • Mozilla

    • Tor ☛ New Alpha Release: Tor Browser 16.0a7 | The Tor Project

      Moreover, Tor Browser Alphas are now based on Firefox's betas. Please read more about this important change in the Future of Tor Browser Alpha blog post.

      If you are an at-risk user, require strong anonymity, or just want a reliably-working browser, please stick with the stable release channel.

• Openness/Sharing/Collaboration

  • Open Data

    • Latvia ☛ Latvia will start exchanging laboratory data with other EU states

      The Latvian Digital Health Centre, in cooperation with the National Health Service, is implementing the project “Exchange of laboratory data of Latvian patients”, the aim of which is to launch a new E-health service; the cross-border exchange of laboratory test results within the European Union (EU).

    • Rlang ☛ Football meets machine learning: Forecasting the 2026 FIFA World Cup

      The forecast is based on a machine learning algorithm that blends a variety of different sources of information: An ability estimate for every team based on historic matches; an ability estimate for every team based on odds from 24 bookmakers; average ratings of the players in each team based on their individual performances in their home clubs and national teams; the average market value of all players in each team according to a wisdom-of-the-crowd approach; further team and country covariates (e.g., FIFA and Elo ratings or GDP). A machine learning algorithm is trained on the results of all major football tournaments (Men’s World Cups and Euros) between 2006 and 2024 and then applied to current information to obtain a forecast for the 2026 FIFA World Cup. More specifically, the algorithm estimates the predicted number of goals for all possible matches between all 48 teams in the tournament. Based on the predicted goals the probabilities for each potential outcome (i.e., 0-0, 1-0, 0-1, 2-0, etc.) in each of these matches can be computed from a bivariate Poisson distribution (here: assuming independence). This allows us to simulate all matches in the group phase and which teams proceed to the knockout stage and who eventually wins. Repeating the simulation 100,000 times yields winning probabilities for each team. The results show that Spain is the favorite for the title with a winning probability of 14.5%, closely followed by England and France, both with 12.4%, and Germany with 11.2%. The winning probabilities for all teams are shown in the barchart below with more information linked in the interactive full-width version.