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By now you’ve seen a lot of stuff being built using ChatGPT. A lot, Jerry. A LOT. I’ve built a few apps and extensions as well, but this is the first I’m writing about. Over the last 3-4 years, “building” software on any scale has seen quite a radical shift. Here’s an image to scale - So when I first tried to build a Chrome extension for a company hackathon in 2022, I took around 12 hours, pulling an all-nighter. I looked up documentation, Stack Overflow answers, sample blogs and trudged through the whole process - The way god intended it. And finally completed…something. The end result was something that did the job I wanted but it looked absolutely horrendous and I had to hand-wave over the UX because I had no time before the presentation. ...

One of the most sought after things to learn right now is about how to set up your own local LLM server and how to use LLM models locally. With the arrival of some things like Ollama and LM Studio etc, it has become very easy. Ollama is an orchestrator that lets you serve up models locally, models like Llama 3.1, Qwen-2.5, Phi, whatever models you have on HuggingFace. These are available to be served up and many more. ...

Now, why do this? What’s wrong with Medium and Substack and Blogger and Wordpress and all the tens of websites out there? Nothing. You could totally just create a blog there and publish. That’s why Content Management Systems exist - so you could focus on the content and not on the management . But if you’re like me and want some more control over how you publish your blogs, customize them etc. , you will find this and the other upcoming articles in this category interesting. ...

Chapter 1 - Reliable, Scalable and Maintainable Applications In [[Reading DDIA - Part 1]] , I read about Reliability. The next section is Scalability . First let me talk about the assumptions I made about the term Scalability, what I understand from it prior to reading Martin Kleppman’s thoughts on the topic - What is a scalable system? My thoughts prior to reading the section - Scale refers to how does a system grow. Growth can be needed for multiple reasons - ...

(Here’s the preface in case you missed it - [[Reading DDIA - Preface]]) Chapter 1 - Reliable, Scalable and Maintainable Applications This chapter’s goal is to effectively give us a high level overview of what this book is fundamentally about - Thinking about data systems along the axes of : Reliability Scalability Maintainability What is a reliable system? My thoughts before reading the section : A system that is available to return results/outputs that are expected of it when it is employed. If I’m accessing an API, if the API is available 99 out of 100 times, then its reliability is 99% If a server is available for 23 hrs 45 minutes per day then its availability is 23.75/24 = 98.9% But is availability == reliability? Let’s see. A reliable human is someone who does something that he says he will do or is expected to do every time. Similarly a reliable system is one that returns the expected results every time that they are used. An ATM is reliable if I can withdraw money from it in the denominations that I want, when I want it. For example, the ATM in Puttenahalli , JP Nagar is perpetually unavailable. Everytime I go there, the system is under maintenance. It is 0% reliable. Let’s read the chapter. ...

Installing Postgres locally and connecting to it from Python First of all, what is Postgres and why do I care? Over the course of our working with data, we come across a lot of ways of storing data - cache, in-mem, files, file based databases, SQL databases, NoSQL databases etc. Each option has a specific set of usecases that are best satisfied by said storage mechanism. Postgres DB is one such storage mechanism - specifically an Open Source, Relational Database. ...

Jupyterlab is a definite improvement on the older IPython notebook interface - both in features and in appearance. There is now even an in-built “Dark Theme” that can be enabled. But is that all? As we know, Jupyterlab is a browser based app and is ipso facto, written on a base of HTML, CSS and Javascript. So if we want to change the appearance over and above what we get out of the box with jupyterlab, we can. Now, it is possible to make any CSS changes by hacking into the internals of the notebook, but thanks to a nifty Jupyterlab extension by Adam Wallner, we don’t have to. ...

Disclaimer : Extensions in Jupyter-lab are still very much experimental. But this one seems to be working fabulously so far. jupyterlab-git is an extension that lets you stage and commit changes to notebooks made right from within the Jupyterlab interface. This is best installed within the confines of a virtual environment, as is anything experimental. Installation steps - a) Ensure that you have the latest version of jupyterlab (=1.2.0 at the time of this writing) and NodeJS(=12.13.0 at this time) ...

I keep Googling commands for some of these situations regularly - General - 1) To find files one level below your current directory - I was trying to find which repos in my set of folders have a setup.py file. So, this is what I’d use. find . -maxdepth 2 -iname setup.py 2) To find what process is running on port 2181 - sudo lsof -n -i :2181 | grep LISTEN ...

I use Ubuntu 16.04 and I’ve been searching for a good memory monitoring desktop widget to no avail. I found a couple of taskbar widgets but none that would tell me the free memory left in addition to the used/swap/cache memories. So I decided to write my own (with loads of help from the Internet of course). Component 1 — The widget I didn’t know how to do this. Thankfully Stuart Langridge had already done this for me. I tweaked the override_background_color parameter to get a red background for my widget and the size of the widget itself to be 400*20 so it would be a nice small strip rather than a big blob of a rectangle. ...

I have watched and re-watched Seinfeld over and over for the last 6–7 years now and it remains, till date, one of my most favorite shows. For a show that claims to be about nothing, it has certainly managed to fill up nine seasons worth of content, all with seemingly no plot. The show, if you’re unfamiliar with it, traces the day-to-day lives of (mainly) 4 quite unremarkable people — Jerry Seinfeld, George Costanza, Cosmo Kramer and Elaine Benes. These 4, along with plenty of other side characters and guest stars engage in what seems to be a series of meaningless conversations and activities, which somehow all come together towards the end of the duration of each episode. ...

Alright. Round 2 . FIGHT! So, the last time, I figured out, unintentionally, at what times of the day most of my posts happened. This time, I again unintentionally got results different from what I set out to do — I’ll get to this eventually I guess, but for now, the objective is obtaining a measure of the number of posts I make per day and thereby see if I can figure out which days of the week have been the most (least?) productive. Of course, this is still a step away from my eventual goal (hopefully Experiment 3 should sort it out). Let’s get to the methodology — ...

Hours of max FB Usage — I originally intended to do something else, but ended up doing this instead — Figuring out at what hours during the day I’ve been most active on Facebook — outliers included. How? Downloaded my entire Facebook data - This can be done using the Facebook APIs or using the less painful way — requesting for a copy of your Facebook data as a zip file from your Settings panel. ...