#770 — October 9, 2025 |
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Ruby Weekly |
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Buckle Up, There’s a New Gem Server in Town: Jared White |
🗣️ Unsurprisingly, this news led to an extensive discussion on Hacker News. |
![]() 🚨 Rails 7.1 Hit EOL On 10/1. Plan Your Upgrade With Our AI 🤖 — No more security updates for Rails 7.1. Get a free Automated Roadmap in minutes. Know what it takes before you start. Need help executing the plan? Our 🌳 Bonsai team can help: Fixed-cost, monthly maintenance by our fractional CTO + senior experts. FastRuby.io | Upgrade Experts sponsor |
Ruby 3.4.7 Released — A release to address a small handful of bugs, but also to update the Takashi Kokubun |
⚡️ IN BRIEF:
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The Little Julik Tarkhanov |
Building a Subcommand Ruby CLI with Just David Bryant Copeland |
How to Use a Local Docker Registry in Kamal — It's great news that support for using a local registry for pushing and pulling app images is coming to the Kamal deployment tool. It’s not in a released version yet, but you can give it a try as it was just merged into the Kamal repo. Josef Strzibny |
Better Ruby Apps Come from Better Logging — Honeybadger Insights transforms your logs into rich events that you can act on. Try it for free → Honeybadger sponsor |
📺 Omarchy – An 11-minute tour of DHH’s 📄 Why and How to Delete Your Old Migrations, Today Julik Tarkhanov 📄 The Experience of a Python Dev Learning Ruby in 2025 Vinay Keerthi 📄 Creating a Kanban Board with Rails and Hotwire Rails Designer |
🛠 Code & Tools |
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Amazing Print 2.0: Pretty Print Your Ruby Objects with Style — A fork of the long-fallow AwesomePrint that continues to get updates and is an essential tool for ‘pretty printing’ Ruby objects. AmazingPrint |
🤖 Rllama: Ruby FFI Bindings for DocuSeal |
⏳ Free and Open Source Time Tracker Built with Rails — Simplistic and practical. Free use; and self-hosting available. Made by the biggest Ruby community in Norway 🇳🇴🐻❄️ Rubynor sponsor |
Rumale 2.0: A Machine Learning Library for Ruby — Offers a similar interface to Python’s Scikit-Learn for working with support vector machines, regression, perceptrons, decision trees, K-means, component analysis, and similar concepts and algorithms. A. Tatsuma |
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📢 Elsewhere in the ecosystem |
A roundup of some other interesting stories in the broader landscape:
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