Introduction

I came across a brilliant writeup on Hacker News about creating a Kindle smart dashboard with automatically updating weather, bus schedules and calendar information. The concept immediately caught my attention - repurposing an old e-reader into a useful household display seemed like the perfect weekend project.

Looking around my house, I realised I had two unused Kindles gathering dust in drawers. These devices have excellent battery life and crisp e-ink displays that are easy on the eyes, making them ideal candidates for an always-on dashboard. Was hoarding all my old tech finally about to pay off?

The original author’s approach was solid: run a cloud-based server that renders the dashboard as HTML, captures a screenshot with Puppeteer, and serves that image to the Kindle. However, I wanted to run everything locally on my Raspberry Pi home server rather than relying on cloud infrastructure. Running a full browser just to capture screenshots felt unnecessarily heavy for my Pi, so I wondered: could I generate dashboard images directly using Python instead?

This turned into an interesting multi-part project that taught me about Kindle hacking, Python image generation, and the quirks of older Linux systems. Here’s how it all came together.

Part 1: Building the Python Dashboard Server

I decided early on that Python would be perfect for this project. It has excellent libraries for image generation, API integration, and web serving - everything I needed to build a flexible dashboard system. The core requirement was simple: generate a dashboard image on demand.

My main design goal was modularity. I wanted a widget-based system where each component of the dashboard could be independently developed and positioned. This would make it easy to add new widgets later or rearrange the layout without rewriting everything.

The images would primarily be generated using Pillow and the server would run with Flask.

The Widget System

Using GitHub Copilot in Visual Studio Code with GPT 4.1, I took a step-by-step approach to build out the application. The AI assistance worked surprisingly well for this type of well-defined task, though I made sure to check each step carefully to avoid any issues. It’s like having a really enthusiastic coding buddy who occasionally goes nuts. Watch them closely.

The architecture I settled on treats each dashboard element as a widget with defined position and size parameters. This makes the layout highly configurable - I can easily move widgets around or resize them by changing a few configuration values.

Here are some of the widgets I implemented:

• Weather Overview: Displays current weather conditions and today’s summary using Pirate Weather’s API. Pirate Weather was recommended by the author of the Kindle dashboard blog post I’d read - it’s free for reasonable usage levels and has a simple, well-documented API.

• 5-Day Forecast: Shows small representations of the next five days with weather icons, rain probability, and high/low temperatures. This gives a quick overview of what to expect for the week ahead.

• Family Calendar: Pulls upcoming events from our Google Calendar using the secret iCal URL that Google Calendar can generate. This was much simpler than dealing with OAuth - just grab the secret address and parse the iCal format.

• Text Widget: Displays either static text or dynamically pulls content from a Google Docs document. For the Google Docs integration, I set up authentication via a Google service account, which provides us an easy and sharable place to save any message we want without deploying the server repeatedly.

• Footer: Shows when the dashboard was last generated and, since the Kindle will display the dashboard full-screen, also displays the battery level that the Kindle passes up in its HTTP request.

All widgets that fetch external data implement caching to avoid hammering APIs when the dashboard refreshes frequently.

Testing and Deployment

After some trial and error getting the layout right and fine-tuning the image generation, I opened the dashboard in a browser and it worked perfectly! Well, “perfectly” might be generous but it only took about 17 attempts to get the widgets aligning properly.

The Python approach proved much lighter than running a full browser stack.

I packaged everything into a Docker container and deployed it to my Raspberry Pi! Off we go!

Part 2: Setting Up the Kindle Client

This is where things got really interesting. Kindles run Linux under the hood, which makes them very hackable. The process varies depending on which Kindle model you have…

Identifying and Jailbreaking the Kindle

I started by figuring out exactly which Kindle I had. KindleModding.org turned out to be an invaluable resource - I looked up my serial number and discovered I had a 4th generation Kindle (2011). This was good news, as the K4 has well-documented jailbreaking procedures.

Following the guides on KindleModding.org, I successfully jailbroke the device. The process was surprisingly straightforward, basically consisting of copying a file to the device! I was expecting to feel like more of an elite hacker and it ended up being slightly underwhelming.

Getting SSH Access

Once jailbroken, I needed SSH access to install the dashboard client. I followed this excellent guide to get SSH up and running.

I did run into one snag - a signing issue that prevented some packages from installing. A quick Google search led me to this Reddit solution that resolved the problem.

For the root password, there’s a handy trick: all Kindle root passwords can be calculated from the serial number using this online tool. Thanks for making it easy, Amazon!

Installing the Dashboard Client

I copied over the kindle-dash-client repository to my Kindle with scp. This provides the scripts needed to fetch dashboard images and display them.

However, I immediately ran into line ending issues. The shell scripts had Windows CRLF line endings that needed to be converted to Unix LF before they would execute properly on the Kindle. This was likely due to my Git configuration on Windows.

SSL Certificate Issues

Another roadblock: curl wouldn’t work properly due to outdated SSL certificates. I had to replace /etc/ssl/certs/ca-certificates.crt with a fresh version from curl.se before HTTPS requests would work.

Configuration and Testing

After updating the shell scripts to point at my Raspberry Pi instead of a cloud server, I ran the test command and… success! The dashboard appeared on the Kindle screen.

I configured the image resolution to match my Kindle’s 600x800 pixel display, and the Python server dutifully generated perfectly sized images.

The rtcwake Challenge

One significant issue emerged during setup: my K4 didn’t have rtcwake available by default. This utility is crucial for properly sleeping the Kindle between dashboard updates. Using alternatives like sleep caused the battery to drain much too quickly.

Fortunately, someone in the community had already solved this problem. I found a K4-compatible rtcwake binary that someone had helpfully compiled and shared. Installing this fixed the power management issues completely. The internet is a great place - someone out there compiled utilities for a 13-year-old e-reader to share with the world.

Final Configuration

After some tweaking of the refresh schedule and fine-tuning the startup scripts, everything was working beautifully. I set the refresh interval to 20 minutes, which provides timely updates without being excessive.

The results exceeded my expectations: the Kindle battery lasts over two weeks between charges! This is much better than I had hoped for, making it practical as a permanent household display.

Part 3: Next Steps

Now that I have one Kindle working perfectly, there are several directions I want to explore:

Second Kindle Setup

I have another Kindle - a 3rd generation Keyboard model (2010) - that I’d like to get running as well. The jailbreak process will be slightly different, but similar client scripts should work once I get it jailbroken. Because why stop at one when you can build a small army of repurposed e-readers?

Enhanced Dashboard Features

The Python server architecture makes it easy to add new capabilities. I’m planning several improvements:

• Better Configuration Management: Make it easier to customize dashboards through configuration files rather than code changes
• Scheduling System: Serve different dashboards based on time of day or day of week. For example, show train schedules during morning and evening commute times on weekdays
• More Widget Types: Train alerts, news headlines, stock prices, or even photos from cloud storage

AI-Powered Development

The modular architecture I built seems like a perfect match for AI coding tools. I’m excited to experiment with building this out further, perhaps even an admin interface to make dashboard configuration more data driven and user-friendly. I’ll definitely get carried away with this and add loads of features I never use.

Power Optimization

While two weeks of battery life is already impressive, I think I can push it even further by reducing the update frequency during overnight hours when nobody is looking at the display.

Wrap Up

This project turned out to be more engaging than I initially expected. There’s something satisfying about breathing new life into old hardware and creating something genuinely useful for daily life. The combination of modern Python development with retro Kindle hacking created an interesting technical challenge that taught me quite a bit about both domains. Another part of my smart home set up held together with Python, shell scripts and duct tape.

If you have an old Kindle lying around, I highly recommend giving this project a try. The results are surprisingly polished and the battery life makes it practical for long-term use as a household information display.