Misc

I like writing custom scripts to automate stuff or fix repetitive headaches. Most of them are shell scripts, and a few of them are written in Python. Over the years, I’ve accumulated quite a few of them. I use Git and GNU stow1 to manage them across different machines, and the workflow2 is quite effective. However, as the list of scripts grows larger, invoking them becomes a pain because the tab completion results get cluttered with other system commands. Plus, often I even forget the initials of a script’s name and stare at my terminal while the blinking cursor facepalms at my stupidity. ...

I’m one of those people who will sit in front of a computer for hours, fiddling with algorithms or debugging performance issues, yet won’t spend 10 minutes to improve their workflows. While I usually get away with this, every now and then, my inertia slithers back to bite me. The latest episode was me realizing how tedious it is to move config files across multiple devices when I was configuring a new MacBook Air and Mac Mini at the same time. ...

This site1 is built with Hugo2 and served via GitHub pages3. Recently, I decided to change the font here to make things more consistent across different devices. However, I didn’t want to go with Google Fonts for a few reasons: CDN is another dependency. Hosting static assets on GitHub Pages has served me well. Google Fonts tracks users and violates4 GDPR in Germany. Google Analytics does that too. But since I’m using the latter anyway, this might come off a bit apocryphal. I wanted to get a few extra Lighthouse points. Turns out, it’s pretty easy to host the fonts yourself. ...

This morning, while browsing Hacker News, I came across a neat trick1 that allows you to share textual data by leveraging DNS TXT records. It can be useful for sharing a small amount of data in environments that restrict IP but allow DNS queries, or to bypass censorship. To test this out, I opened my domain registrar’s panel and created a new TXT type DNS entry with a base64 encoded message containing the poem A Poison Tree by William Blake. The message can now be queried and decoded with the following shell command: ...

This weekend, I was working on a fun project that required a fixed-time job scheduler to run a curl command at a future timestamp. I was aiming to find the simplest solution that could just get the job done. I’ve also been exploring Google Bard1 recently and wanted to see how it stacks up against other LLM tools like ChatGPT, BingChat, or Anthropic’s Claude in terms of resolving programming queries. ...

One of my favorite pastimes these days is to set BingChat to creative mode, ask it to teach me a trick about topic X, and then write a short blog post about it to reinforce my understanding. Some of the things it comes up with are absolutely delightful. In the spirit of that, I asked it to teach me a Shell trick that I can use to mimic maps or dictionaries in a shell environment. I didn’t even know what I was expecting. ...

I needed to compare two large directories with thousands of similarly named PDF files and find the differing filenames between them. In the first pass, this is what I did: Listed out the content of the first directory and saved it in a file: ls dir1 > dir1.txt Did the same for the second directory: ls dir2 > dir2.txt Compared the difference between the two outputs: diff dir1.txt dir2.txt This returned the name of the differing files likes this: ...

Whenever I need to whip up a quick command line tool, my go-to is usually Python. Python’s CLI solutions tend to be more robust than their Shell counterparts. However, dealing with its portability can sometimes be a hassle, especially when all you want is to distribute a simple script. That’s why while toying around with argparse to create a dynamic menu, I decided to ask ChatGPT if there’s a way to achieve the same using native shell scripting. Delightfully, it introduced me to the dead-simple select command that I probably should’ve known about years ago. But I guess better late than never! Here’s what I was trying to accomplish: ...

When writing shell scripts, I’d often resort to using hardcoded ANSI escape codes1 to format text, such as: #!/usr/bin/env bash BOLD="\033[1m" UNBOLD="\033[22m" FG_RED="\033[31m" BG_YELLOW="\033[43m" BG_BLUE="\033[44m" RESET="\033[0m" # Print a message in bold red text on a yellow background. echo -e "${BOLD}${FG_RED}${BG_YELLOW}This is a warning message${RESET}" # Print a message in white text on a blue background. echo -e "${BG_BLUE}This is a debug message${RESET}" This shell snippet above shows how to add text formatting and color to shell script output via ANSI escape codes. It defines a few variables that contain different escape codes for bold, unbold, foreground, and background colors. Then, we echo two log messages with different colors and formatting options. ...

I’ve always had a vague idea about what Unix domain sockets are from my experience working with Docker for the past couple of years. However, lately, I’m spending more time in embedded edge environments and had to explore Unix domain sockets in a bit more detail. This is a rough documentation of what I’ve explored to gain some insights. The dry definition Unix domain sockets (UDS) are similar to TCP sockets in a way that they allow two processes to communicate with each other, but there are some core differences. While TCP sockets are used for communication over a network, Unix domain sockets are used for communication between processes running on the same computer. ...

The colon : command is a shell utility that represents a truthy value. It can be thought of as an alias for the built-in true command. You can test it by opening a shell script and typing a colon on the command line, like this: : If you then inspect the exit code by typing $? on the command line, you’ll see a 0 there, which is exactly what you’d see if you had used the true command. ...

After reading Simon Willison’s amazing piece1 on how he adds new features to his open-source softwares, I wanted to adopt some of the good practices and incorporate them into my own workflow. One of the highlights of that post was how to kick off a feature work. The process roughly goes like this: Opening a new GitHub issue for the feature in the corresponding repository. Adding a rough description of the feature to the issue. ...

My grug1 brain can never remember the correct semantics of quoting commands and variables in a UNIX shell environment. Every time I work with a shell script or run some commands in a Docker compose file, I’ve to look up how to quote things properly to stop my ivory tower from crashing down. So, I thought I’d list out some of the most common rules that I usually look up all the time. ...

TIL that returning a value from a function in bash doesn’t do what I thought it does. Whenever you call a function that’s returning some value, instead of giving you the value, Bash sets the return value of the callee as the status code of the calling command. Consider this example: #!/usr/bin/bash # script.sh return_42() { return 42 } # Call the function and set the return value to a variable. value=$return_42 # Print the return value. echo $value I was expecting this to print out 42 but instead it doesn’t print anything to the console. Turns out, a shell function doesn’t return the value when it encounters the return keyword. Rather, it stops the execution of the function and sets the status code of the last command in the function as the value that the function returns. ...

Whenever your local branch diverges from the remote branch, you can’t directly pull from the remote branch and merge it into the local branch. This can happen when, for example: You checkout from the main branch to work on a feature in a branch named alice. When you’re done, you merge alice into main. After that, if you try to pull the main branch from remote again and the content of the main branch changes by this time, you’ll encounter a merge error. Reproduce the issue Create a new branch named alice from main. Run: ...

Whether I’m trying out a new tool or just prototyping with a familiar stack, I usually create a new project on GitHub and run all the experiments there. Some examples of these are: rubric: linter config initializer for Python exert: declaratively apply converter functions to class attributes hook-slinger: generic service to send, retry, and manage webhooks think-async: exploring cooperative concurrency primitives in Python epilog: container log aggregation with Elasticsearch, Kibana & Filebeat While many of these prototypes become full-fledged projects, most end up being just one-time journies. One common theme among all of these endeavors is that I always include instructions in the readme.md on how to get the project up and running—no matter how small it is. Also, I tend to configure a rudimentary CI pipeline that runs the linters and tests. GitHub Actions and Dependabot1 make it simple to configure a basic CI workflow. Dependabot keeps the dependencies fresh and makes pull requests automatically when there’s a new version of a dependency used in a project. ...

I run git log --oneline to list out the commit logs all the time. It prints out a compact view of the git history. Running the command in this repo gives me this: d9fad76 Publish blog on safer operator.itemgetter, closes #130 0570997 Merge pull request #129 from rednafi/dependabot/... 6967f73 Bump actions/setup-python from 3 to 4 48c8634 Merge pull request #128 from rednafi/dependabot/pip/mypy-0.961 5b7a7b0 Bump mypy from 0.960 to 0.961 However, there are times when I need to list out the commit logs that only represent the changes made to a particular file. Here’s the command that does exactly that. ...

While working on a project with EdgeDB1 and FastAPI2, I wanted to perform health checks against the FastAPI server in the GitHub CI. This would notify me about the working state of the application. The idea is to: Run the server in the background. Run the commands against the server that’ll denote that the app is in a working state. Perform cleanup. Exit with code 0 if the check is successful, else exit with code 1. The following shell script demonstrates a similar workflow with a Python HTTP server. This script: ...

I was browsing through the source code of Tom Christie’s typesystem1 library and discovered that the shell scripts2 of the project don’t have any extensions attached to them. At first, I found it odd, and then it all started to make sense. Executable scripts can be written in any language and the users don’t need to care about that. Also, not gonna lie, it looks cleaner this way. GitHub uses this [pattern]3 successfully to normalize their scripts. According to the pattern, every project should have a folder named scripts with a subset or superset of the following files: ...

One thing that came to me as news is that the command which—which is the de-facto tool to find the path of an executable—is not POSIX compliant. The recent Debian debacle1 around which brought it to my attention. The POSIX-compliant way of finding an executable program is command -v, which is usually built into most of the shells. So, instead of doing this: which python3.12 Do this: command -v which python3.12 Debian’s which hunt ↩︎ ...