I wanted to assemble four of those 64x64mm RGB matrix panels. However, my 3D printer is limited to about 250x205mm, and the panels are 256x256mm.

It required a little creativity, but I devised a single print of about 249x136mm such that by printing two and flipping one of them over, it becomes a bracket that can hold the four panels together.

I have a feeling that the injection molded bodies of these panels may change from time to time, potentially moving the screw & post positions. My 4 panels were purchased around February 2025.

I developed the part in OpenSCAD, Free (GPL) 3D modeling software available on Linux, Mac, & Windows. To create a 3D printable STL file, open the SCAD file, press F5 to "render" it to triangles, and then F7 to export to STL.

Overview

One of the coolest things about Solder Party's Keyboard Featherwing is its versatility. While it offers a fully-featured hardware package all on its own, the ability to pair it with any Feather board allows it to be extended to do pretty incredible things. In this project, I'm pairing it with a Feather nRF52840 Express to create a universal Bluetooth Low Energy (BLE) keyboard/mouse/remote control, programmed in CircuitPython.

Using the nRF52840, CircuitPython has the ability to send BLE keyboard, mouse, and consumer control HID events to control a host device, such as a computer. This firmware combines the ability to send all 3 event types from a single device in an easily configurable way, adding another layer of versatility!

Some possible applications:

• Control a laptop connected to a TV remotely, with physical keyboard and full mouse support
• Control an Apple TV, including navigation. Use a physical keyboard when searching!
• Remotely trigger the camera shutter on iPhone/iPad
• Use the 9 programmable buttons to make a BLE "macro pad"
• Practically anything that could benefit from a BLE keyboard, mouse, and/or consumer control remote

Another nice thing about the nRF52840 for this application is its excellent energy efficiency. When using a 2000mAh LiPo battery, I've been able to get between 70-80 hours of active use on a single charge! The Keyboard Featherwing's built-in on/off switch allows extending the battery life even further.

Firmware Features

• Compact physical keyboard makes it easy to type wirelessly on device like laptops/desktops, Raspberry Pis, or anything else that can connect to BLE keyboards.
• Touch screen behaves as a trackpad/mouse when connected to a host device that supports pointer devices.
• 4 activity presets, selectable through an on-screen preferences menu. Further configuration is possible by connecting device to a computer via USB and editing the configuration files in the user directory.
  • Each activity allows you to customize the 4 function buttons and the 5-way direction button (D-BUTTON) to send keyboard, consumer control, and mouse button events
• Adjustable display/keyboard/NeoPixel brightness
• Adjustable primary user interface color
• Power-saving feature: auto-dim keyboard, screen, and NeoPixel after 30 seconds of inactivity, significantly increasing battery life.
• Battery voltage monitoring and "needs charge" indicator.

If you're working an office job, you're...in an office. Whether that's in your home or not, I'm going to hazard a guess that it's also indoors - and being indoors for an extended period of time without well-ventilated spaces can legitimately lead to low air quality (and in theory health issues).

Now, I'm not hear to spread fear and make you all think you're dying a slow death by breathing in your co-worker's exhalations. However, I am here to show off an easy way to build a cloud-connected indoor air quality system with:

1. A variety of Adafruit air quality sensors.
2. A Blues Notecard to cloud-connect the project with LTE connectivity.
3. Adafruit IO to visualize air quality data and integrate with other services.
4. A Philips Hue LED strip to provide real-time visuals for low air quality alerts.

Gradient is a node-based editor designed for use with Autodesk Fusion 360. 

I started working on Gradient after playing with the node based geometry in Blender. The nodes in Blender are fantastic (frankly they work much better than mine do right now) but I wanted  to create algorithmically defined geometry right in Fusion 360 using solids and surfaces which are better suited to making 3D models for technical and engineering parts. I wanted to be able to make algorithemic structures that are user defined but and can be finely controlled and tuned to the design needs.

Models like this would be very time consuming to model by hand. However they can be quickly generated and re-generated with different parameters or random seeds.

If you are interested in trying Gradient for yourself you can download it from the github repository below. Please be aware currently Gradient is in an early development stage, meaning only a small fraction of its functionality has been implemented, and there are likely a few bugs to sort through.

Gradient github

I really enjoyed getting my first PyBadge because it gave me a way to make my own arcade games using https://arcade.makecode.com. I did find that, I actually like making the games even more than playing them, so I thought about ways to have someone (or something) else play the game.

I'd heard about the idea of "mouse jigglers" - mechanical or software cheats to make it look like you were busy working on a computer when you weren't, and I knew CircuitPython supported HID (Human Interface Device) so I could send keystrokes. So why not "let C3P0 take the wheel"?

That led to my simple "mouse jiggler" for playing arcade games in a browser. (https://en.wikipedia.org/wiki/Mouse_jiggler) (Yes, this actually is a keyboard jiggler that randomly "fires" by sending spaces, and maneuvers by randomly sending cursor keys up, down, left and right.)

Designed to take over playing a simple arcade game in a browser, for example: https://makecode.com/_JfAKKf2EUcLv This game lets you steer the Millenium Falcon, and shoot asteroids and Star Destroyers.

Touch #1 on the NeoTrinkey to fire lasers, and touch #2 to toggle on/off a random "jiggler" that continuosly moves the ship around, randomly shooting.

Touch #1 and #2 together to end program.

Flashes green when autopilot is engaged, and red when it ends. Ending program flashes gold.

Program file:

AutoPilot.py - copy to code.py on the neotrinkey.

 

Github repo HERE

IMPORTANT NOTE: Programming  something like this, using the HID interface can be tricky, as having a program randomly spewing spaces, and cursor keys will mangle any text you are editing. When I wrote this, the initial testing had touching #2 just call the jiggle() function. That way I didn't have a program going crazy and messing with the program text. Once it was working, it was safe to build the loop  that would continuously call jiggle() and shoot().

I had an Adafruit Huzzah and an OLED FeatherWing 128 x 64 in my box of goodies and decided to make a smart digital clock for my study.

The clock is connected to internet via WiFi, synchronises the time and via an api displays the temperature in my area. It is set to update every 5 minutes. Also displays an icon of the current weather. 

These are parsed from the api response:

{"coord":{"lon":yyyyyy,"lat":xxxxx},"weather":[{"id":800,"main":"Clear","description":"clear sky","icon":"01n"}],"base":"stations","main":{"temp":1.03,"feels_like":-1.33,"temp_min":0.57,"temp_max":2.64,"pressure":1039,"humidity":76,"sea_level":1039,"grnd_level":1034},"visibility":10000,"wind":{"speed":2.06,"deg":170},"clouds":{"all":0},"dt":1738790391,"sys":{"type":1,"id":1440,"country":"GB","sunrise":1738742403,"sunset":1738773892},"timezone":0,"id":3333224,"name":"xxxxxx City","cod":200}

Next I created a 3D printed bezel that allowed me to fit the stacked boards in my workbench pannel.

As part of a series on Zephyr with Adafruit hardware, this guide shows how to configure Zephyr to use an ST7789 TFT display with a Feather RP2350. By connecting the display with a breadboard, we can use a logic analyzer to verify that the Zephyr display driver pin configuration agrees with the CircuitPython display driver. This guide is meant for people interested in adding support for Adafruit displays to Zephyr.

Parts

jq for all...?

If you've not heard of or used `jq`, then count yourself lucky, as it is the tool of choice for data scientists up a creek with no paddle... If you find yourself wresting a 2GB JSON file then you'll probably end up using jq to help. See more details of the jq command-line tool at https://jqlang.org/

Using jq can be really quick and simple, but sometimes finding the right incantation to return a subset of the data can leave you feeling a bit like you've been learning FFMPEG (another great tool where I found myself deep in a tutorial one weekend).

Don't do it yourself, get AI to write that query!

Fortunately we live in the days of Large Language Models ("AI" LLMs), which like nothing more than answering humans need for the correct FFMPEG/jq arguments to solve some "critical" problem.
So don't feel like you need to learn the syntax, just throw your data and desired output format at the machines and ask for the jq syntax to achieve that!

Here's an example where I threw a slightly truncated version of the 80kb json at chatGPT and asked for the output format I wanted: https://chatgpt.com/share/67c1c7a6-bf5c-8000-823c-d422593d2ed8

There's also a jq playground website, allowing you to submit your JSON and "query" or fetch the data from a website URL, and it runs entirely in the browser (WASM version of jq) at https://play.jqlang.org/

 

It's great, but not what I was looking for... I needed something that would allow a microcontroller with very little RAM (random access memory) to get some values from large JSON payloads, without having to download and process all the JSON data just to find a couple of values.

Microcontrollers are usually too underpowered to load a full web browser with javascript and WASM support, so ideally we need something more like a web-service that would allow a simple web request to trigger all the work and return the subset of data we're looking for.

 

Estimate Pi with the Monte Carlo method and a neotrinkey

The power of randomness can be harnessed! Estimating the area of a circle by throwing darts at random gives you the means to estimate the value of Pi! I first learned about using the Monte Carlo back in the '80's and even used it in software development to estimate timing of events. You can use it with you NeoTrinkey to estimate the valueof Pi. You can find my github repository here: https://github.com/mrklingon/PieceOfPi/

Monte Carlo methods are a broad class of computational algorithms that rely on repeated random sampling to obtain numerical results. One of the basic examples of getting started with the Monte Carlo algorithm is the estimation of Pi. (https://www.geeksforgeeks.org/estimating-value-pi-using-monte-carlo/)

This project iterates over a unit circle of radius one and "throws" darts at random from -1 to 1 x, and -1 to 1 y, then counts how many land IN the circle. Pi is estimated by multiplying 4 * "darts inside circle"/all darts thrown

The more iterations (darts) thrown, the closer you approach the value of Pi.

The program runs continuously, pausing 5 seconds between runs. While the program is running/estimating, the neopixels flash random colors. When it finishes an estimate, the neopixel displays the answer by blinking the neopixels green for the value (three times for three, one time for one and so on.). Zeroes are indicated by turning all pixels pink briefly. The pixels flash blue to indicate the decimal point.

If the program is run inside a REPL like Mu, it will print out the results:

 I will estimate Pi.
it is around : 3.14139
I will estimate Pi.
it is around : 3.13818
I will estimate Pi.
it is around : 3.13422
I will estimate Pi.
it is around : 3.1313 

The default value of Iterations is 100 - you can change that to higher or lower values.

Files

• findPi.py - copy to code.py to run
• ncount.py - helper file, provides color definitions and blinknum() to blink the digit values.

For more about the Monte Carlo Method: https://en.wikipedia.org/wiki/Monte_Carlo_method

Overview

Physical controls for a more enjoyable media playback experience.

Features

• Responsive volume knob & mute button.
• Transport controls (play/pause, stop, FF/REW, skip tracks).
• Pair up with your favourite Bluetooth® speakers.
• Quick, physical connection (don't have to go through menu system to pair with keypad & speakers).
• Customizable controls/scheme.
• Customizable setup: Optionally connect USB hub/dock for added features, for example:
  • mirror phone to TV w/HDMI out: Watch videos on a bigger screen
  • add keyboard: Better typing experience for texts/emails.
• Solderless project.

Main hardware

Program your device

To get your RP2040 macropad to act as a media controller, it needs to:

1. detect keypresses and changes in the knob position
2. send out corresponding keyboard messages to the attached USB host device (ex: a phone).

My own implementation for this "media hub" is written for Adafruit's CircuitPython, and can be found here:

• 💾 MediaController project README (see MediaHub_AFMacropad). 🚀 Installation instructions.

As part of a series on Zephyr with Adafruit hardware, this guide shows how I made a pogo pin SWD debug probe adapter for the CLUE board so I can conveniently program it with Zephyr firmware. My other SWD option was soldering wires to the test points, but I like how pogo pins are neater and less fragile. This guide is meant for people interested in adding support for Adafruit boards to Zephyr. It might also be useful for folks who want to fix a bricked bootloader.

Overview

As part of a series on Zephyr with Adafruit hardware, this guide shows how to write a Zephyr board definition for the Adafruit Feather RP2350 with an I2C SHT41 temperature and humidity sensor. Future guides will look more at using sensors and displays. This is intended for developers who want to know about adding support for Adafruit boards to Zephyr. If you just want to write CircuitPython code, you can safely ignore this stuff.

Overview

The OM Weather Display periodically updates and displays the following local weather conditions:

• Day, date, and time (AM/PM)
• Tomorrow's sunrise and sunset times
• Temperature
• Relative Humidity
• Wind speed and direction
• Wind gust speed
• Condition description and graphic icon

Location, time zone, and measurement units settings are stored in the settings.toml file. Either "METRIC" or "IMPERIAL" measurement units can be specified.

Weather condition query and internet clock refresh interval rates are set by parameters in the code.py module. The default interval for updating weather conditions is 5 minutes. The local time is updated from the Adafruit Network Time Protocol (NTP) server hourly.

The CircuitPython code runs on an ESP32-S3 4MB/2MB Feather attached to a 2.4-inch TFT FeatherWing. An optional ALS-PT19 ambient light sensor can be used to automatically adjust display brightness.

CircuitPython Code

The Weather Display's CIRCUITPY root directory contains the following files and folders.

• files:
  • settings.toml -- Wi-Fi and location parameters
  • om_query.py -- OM API URL query string builder
  • who_to_map_icon.py -- parses the WMO weather code for descriptions and icons
  • code.py -- the primary code module
• folders:
  • fonts -- contains the font files
  • icons_160x160 -- the weather icon bitmap graphics files
  • lib -- the CircuitPython library modules
  • sd -- a placeholder for the unused SD storage drive

A downloadable bundle of code files and folders can be found in the OM Weather Display GitHub repository.

Materials

The following parts are used to build the MiniMarquee:

• QT Py ESP32-S2
• IS31FL3741 13x9 PWM RGB LED Matrix
• 50mm Stemma QT cable
• Black LED acrylic, 2-3 mm thick, cut to 41mm x 29mm
• 4 M2x12 nylon screws and nuts
• Little rubber feet
• Nitto double-sided adhesive tape (or other tape with similar adhesive strength)
• 2 1-ounce wheel weights (optional)

Installing Firmware

The MiniMarquee's firmware is written for Arduino in PlatformIO. There are two ways to install the firmware onto the QT Py ESP32-S2:

1. Drag-and-drop UF2 installation
2. Build source code and install onto device

The UF2 method is recommended, as it is very simple and does not require downloading any additional software or dealing with any code at all. However, if you wish to customize your MiniMarquee's firmware, you'll need to go for option 2 and build it from source.