Yay computers!
Because I missed a tab in a Python script, my home Docker box has been running with a higher-than-necessary CPU utilization and spiky temperatures for five months. 😬
Tab has now been tabbed. 🐍
Watch your tabs!
Snake Eyes + Servos
Carve Different
Squishy buttons!
Faux Notch Fun
I’ve seen a lot of these little “fake notch” apps pop up since Apple’s new MacBooks were announced, but I didn’t see a lot of source code – so of course I was nerd sniped.
Here’s a basic example of making one using AppKit and SwiftUI!
Wyze Cam in iOS
Joining Automattic
I’m thrilled to be joining the fine folks at Automattic this month as a mobile software engineer. Though I’ll miss all of my wonderful Clemson coworkers immensely, I’m excited for the road ahead. 🚀
Flip Dots!
I saw flip dots (also called flip discs) last year for the first time and instantly knew I needed some in my life. If you’re not familiar with them, check out how they work!
The particular model I have is the ALFAZETA XY5, which may be the easiest way to get up and running, but certainly not the least expensive.
After getting the board, all you need is:
- 24V power supply
- Something that talks over RS485 (in my case I used an ESP8266 connected to a MAX3485 board)
- Their documentation that defines the controller data protocol
I plan to write in more detail how it all works, but for this demo the stack is:
- SwiftUI app that runs SwiftGFXWrapper (which is mainly Adafruit’s GFX Library under the hood)
- The app sends the entire pixel buffer over UDP to the ESP8266
- The ESP8266 sends data to the XY5 over RS485 using their controller’s protocol
Playground support for SwiftGFXWrapper
For even easier prototyping, I’ve added Swift Playground support to my SwiftGFXWrapper project!
Scraping an Arris cable modem status page
It felt good to complete this project that’s been on my list for quite some time. The main goal was to scrape the values from my modem’s status page and pipe them into InfluxDB, which feeds Grafana. Not only could I look at data trends, but I could receive alerts if certain values exceeded an acceptable threshold.
Overall this is a straightforward process:
- Pull in the HTML from the status page (which happens to not need any authentication, making it even easier)
- Parse the tables we care about (Downstream and Upstream) using XPaths
- Munge the data into something suitable for InfluxDB
- Insert the data into InfluxDB
- Query the InfluxDB data from Grafana
I knew I wanted to use Python for the project, so I first looked into Scrapy. After wrapping my mind around it (somewhat) I gave it a go and actually had a working solution… but it felt way over engineered and at times inflexible for what I wanted. I threw 90% of that solution away and went with a simpler script.
What I landed on was something that’s custom and lightweight, but extendable in case someone has a different status page or wants to use an alternative to InfluxDB.
