April 05, 2026

Project 86: TypeMySpeed is Live!

Taming the Matplotlib Beast: My Journey Through Data Viz and Tkinter

It’s Day 86 of my coding journey, or as I’ve started calling it: "The Great Python Consolidation." 🐍 The assignments are getting trickier, but my "just one more feature" addiction is officially in full swing.


For this milestone, I built TypeMySpeed — a desktop speed-typing app inspired by the classics like TypingTest.com. While professional versions are built by entire teams over months, I decided to see how much "pro" functionality I could cram into a solo build.


I started by architecting the three stages of the UI (Config, Test, and Results). The real brain-teaser was data management. Since this was headed for an .exe release, I couldn't just hardcode data inside the app. I had to learn the "grown-up" way of handling files: Local AppData storage. It’s officially a real piece of software now!


Building the main text engine was surprisingly smooth. I spent a good chunk of time on the "Maths of Speed," perfecting the logic for WPM, Accuracy, and Net WPM.


Then came the data visualization. I’ll be honest: I used Pandas to manage the results, which felt a bit like using a sledgehammer to crack a walnut... but hey, it worked!


The real final boss? Matplotlib. I’m convinced that every time you open Matplotlib, you automatically become a novice again. The documentation is a vast, beautiful ocean where you can still somehow drown while looking for a simple "how to change the color of this one bar" tutorial. However, seeing those charts render perfectly inside a TkInter canvas made the gray hairs worth it.


TypeMySpeed is officially out in the wild, but the roadmap is already growing:


  1. Multi-User Support: Because right now, the app thinks everyone is me.
  2. The Cloud: Moving from "Save on PC" to "Save on the Web."
  3. UI Polish: Making it look even sleeker.


Check out the release and let’s see if you can beat my high score!

Tech Stack & Tags
TKInter Pandas Matplotlib
Repository & Link