slaptijack

Merges often bring in massive changes — sometimes dozens of commits and hundreds of lines of code — and the first thing developers ask is: “What just happened?”

Wouldn’t it be great if Git could summarize what a merge brought in, in plain English, right after you run git pull or …

Keeping changelogs up to date is one of those development chores that everyone agrees is important… and everyone forgets to do. Manual changelog curation often falls behind or gets skipped entirely. But what if your Git workflow could automatically generate changelog entries, summarize diffs intelligently, and update your CHANGELOG.md …

Now that you’ve got a fully functional, Python-powered Git hook CLI backed by OpenAI, the next step is sharing it — the right way. A downloadable GitHub repo template helps your teammates (or the open-source world) clone, customize, and integrate the tooling into their own workflows with minimal friction.

In …

Building a local Git hook with Python is great, but if you want others on your team (or across multiple repos) to use it, you’ll want to package it as a reusable command-line tool. In this article, we’ll turn our AI-powered Git hook into a proper Python CLI …

Git hooks are one of the most powerful — and most underutilized — features in the Git ecosystem. They allow you to automate actions at key points in your Git workflow: before committing, before pushing, after merging, and more. Traditionally, these hooks are implemented using shell scripts, but that’s limiting in …

GitHub Copilot is impressive, but what if you could build your own AI-powered Git assistant tailored to your workflow? In this article, we’ll walk step-by-step through building a command-line Git assistant using Python and OpenAI’s API. It will explain diffs, write commit messages, generate .gitignore files, and even …

GitOps has already transformed how we think about infrastructure: declarative, auditable, and version-controlled. But as infrastructure-as-code (IaC) adoption grows and systems become more complex, even GitOps can feel overwhelming.

Enter the next wave: AI-powered GitOps. By integrating large language models (LLMs) into our CI/CD pipelines, infrastructure management becomes not …

Rebase and merge are not rival moral systems. They create different commit graphs, and the useful choice depends on who already depends on the history. Choose the shape that makes collaboration, debugging, and recovery boring—not the one that wins an argument in a pull request.

The graph is the …

Source Code Management (SCM) has evolved dramatically over the past few decades. What started as simple file versioning systems has transformed into sophisticated platforms integrating AI-driven automation, security, and collaboration features. From the days of CVS and SVN to the dominance of Git and the rise of AI-powered development, this …

When working with Google Cloud Storage (GCS) via gsutil, most file operations run smoothly. However, occasional cryptic error messages may appear that leave you scratching your head. One such error is:

Semaphore released too many times MiB]  99% Done
CommandException: 1 files/objects could not be copied/removed.
make: *** [Makefile …

In a previous article, we explored how to count lines of code by language using tools like cloc. While cloc and similar tools are convenient, sometimes you may prefer to avoid additional dependencies and rely solely on standard Unix utilities. Maybe you’re working in a minimal environment, or you …

Count lines of code by language with cloc, tokei, and Git-aware exclusions so generated files, dependencies, and vendor code do not distort your repository metrics.

When working with large Bazel code repositories, it’s not always clear how targets are distributed across directories. Understanding how many targets each top-level directory contains can help gauge complexity, identify hotspots, or guide refactoring efforts.

While Bazel itself doesn’t have a direct command to provide a “count of …

Over the course of this series, we’ve explored how to build client/server applications with Thrift and Protobuf/gRPC in three different programming languages: Java, Rust, and Python. We started with Thrift, implementing a Java server and Python client, then added Rust into the mix. Next, we recreated a …

We’ve now built similar RPC setups using Thrift and Protobuf/gRPC in Java and Python. Following the pattern established with Thrift, let’s integrate Rust into our Protobuf/gRPC ecosystem. Rust’s performance and safety features make it a popular choice for high-performance back-ends, and this exercise will show …