Inspiration

This is a piece of "found art"; a multi-colored circuit board hiding inside some old discarded electronics.  It just needed a backlight and a frame to highlight its beauty.  From the beginning, I knew this would become a nightlight and held onto the board until I had acquired the perfect combination of discarded LEDs and a few other components needed to make it shine.

Case Design

My 3D printed case had 3 chambers.  One for the electronics, one for the LEDs, and a thin slot a the front to hold the circuit board and clear plastic cover.  The reason for the separation was to make sure the LEDs were the right distance to illuminate the board and to minimize the light that leaked out that back of the frame while still allowing hot air to escape.  The design was almost perfect, but I ended up having to cut a large slot in the back so I could replace the back wall with a slotted version for better ventilation (not pictured).

Before closing up the case, test that it can be dimmed appropriately.

Below is a test of the Playground Note code embed directly from Github (must be .md or .py file).  If you see the full code below it is working as intended.  If the example in the library gets updated this Playground Note might not be kept up to date with future changes. The code below will always be the most up to date as it is pulled directly from the adafruit_requests examples library.

Full Example Code

• An uncomprehensive & comprehensible guide to using Adafruit Requests with web API's.

The amount of online API examples for the Adafruit_Requests library is growing. If you're interested in using an API but an example does not exist and you're unsure how to start I will help walk you through the process.

I wrote the majority of the web API examples currently in the examples directory. I'm a pretty good source on how to approach a new unknown web API and wrangle out some basic data. 

JSON

Data is malleable, it can be shaped and formed in a variety of ways.  The most common format currently used with REST API's is JSON. The Adafruit_Requests library is particularly good with JSON data.  If you don't know how to read or write in JSON don't worry, you won't need to.  The library handles all the format conversions for you.  All you need to know is how to get at the data you want and I will walk you through how to do that.

Before we begin there are some glossary terms that you'll need to know in order to make sense of JSON for the web.

REST

Representational State Transfer (REST) is a software architecture that imposes conditions on how an API should work. Most web API's use the REST architecture.  All a beginner needs to know about REST is it's the way a website allows you to retrieve data from an API.

Endpoint

An endpoint refers to the data to retrieve from an API. This can be part of the JSON heirarchy path or a key:value pair. For web API's typically this refers to the JSON Key:Value pair.

Key:Value

• Key:Value (always a pair separated by a colon)

A key is a unique identifier associated with data and the value is the actual data.  An example would be if you're working with a weather API and might want to return current:temperature for a geographic area to display freedom units on a TFT. It would return as `current:70.0` (in Fahrenheit) or if you're living in a sensible country using the metric system it would return `current:21.1` (in Celsius). 

Key Error

It's useful to know the above terms because an error that a website or Circuit Python might return is `invalid key:value pair` or simply `key error`. That error means you requested a key:value that does not exist, you spelled it incorrectly, or the request was otherwise incorrectly formatted.

Inspiration

This project is an extension of the original doggy buttons project where I'll be showing how to make a public dashboard that publishes everything my dog says.  This project is just one example of how to extend the features of my doggy buttons and perhaps one of the silliest IOT devices ever made.  If you want to know about the buttons themselves, see the original project writeup.

With a project like this, it's also important to think about privacy.  I don't want my dog making it possible to tell when we're away from home, so I'll also show how to add a delay so that activity is only published once it's sufficiently stale.

Setup Challenges

User Space vs Admin Space

The first version of my program was kicked off by /etc/rc.local on boot, but this had the side effect of running the program as root.  That was fine for my original project, but I had followed best practice and not used sudo when pip3 installing the Python libraries needed for loading data to AdafruitIO.  If I logged in to run the program as my user, it would end when I logged off but root no longer had all the Python libraries needed to run.

Lennart (Binary Labs) suggested the simple and elegant solution of adding sudo -u MY_PI_USERNAME before the command that would launch my code in /etc/rc.local.  This allows the program to be run as my user without having to login and was much simpler and cleaner than the other solutions I was considering.

Concurrency

The first version of my code simply added a call to aio.send_data(...) in the same loop that processed button presses, but I quickly discovered that the upload process could take 3 - 4 seconds leading to very delayed sounds when more then one button was pressed.  Things like "water outside walk later" became "water ... outside ... walk ... later".  This was starting to confuse my dog because the sounds weren't immediately connected with the button presses and would sometimes sound when she had gone to push something else entirely because the button "wasn't working".

To fix this it was going to be necessary to introduce separate queues, one for playing sounds that could respond quickly, and one for uploading button presses that could slowly upload data to AdafruitIO in the background.

Need to add a simple diagnostic display to a Pico project? Or perhaps you want a quick and easy NeoPixel light show? Let's see what we can do!

Equipment

• Pi Pico board with headers
• NeoPixel Stick 
• Header Pins
• Under Plate PiCowBell

Intro to the RA8875 Driver Board for Circuit Python

The Adafruit RA8875 driver in Circuit Python does not currently support displayio.  You must use read/write registers with a barebones ra8875 graphics library. The current feature set and how it is used is only for very advanced users. 

You can draw a bmp image and overlay text but you'll quickly find that's about all you can do with it.  There are only 2 examples provided and the driver board is unlike any other display device for Circuit Python. Any knowledge you have of displayio does not transfer over to this board; the RA8875 is unique.

The interest of using an 800x480 bare display with Circuit Python is typically due to the sheer size of it but it should come with fair warning:  You must be capable of programming with circuit python from scratch without displayio.

The bits and bytes of binary color

Since the RA8875 can only display a maximum of 16-bit color; the 24-bit image must be converted to 16-bit (color565).

The RA8875 stores color information in its memory with 2 bytes (2 pairs of 8 bits).  Here is a binary representation of how it stores the color. 11111111 00000000  There are 8 bits in 1 byte.

However the RA8875 actually stores them in what is known as swapped color565.  Each first byte must be swapped with the 2nd. This is not some type of color conversion error. These are the direct reads from the memory addresses for the stored colors. 

This is a project that was years in the making, I went through many iterations that failed one way or the other. However, the final project was only started about a few months ago. It's great to see this project realized at last! The trigger really works, it has the appropriate sound effects, it has two firing speeds, and a "virtual ammo" system that you replenish by physically removing and reinserting the cartridge. So, where did it all begin?

The initial step of the process was to design the 3D printable case, which I did in blender. I found someone who extracted a model of the Necrochasm from the game itself and went to work sculpting out the finer details, hollowing out the interior, and adding LED areas. I also took this time to log into Destiny, and use my in-game Necrochasm to record the proper sound effects.

I exported the resulting pieces from blender to fusion 360 where I added the hardware mounting features. My vision for this prop was to have one area where most of the electronics were stored. This trapezoidal area at the bottom-front of the prop looked like it had the most storage capacity.

The CG-35 is a CircuitPython emulation of the Hewlett Packard HP-35 Scientific Reverse-Polish Notation (RPN) calculator designed for the Adafruit ESP32-S3 Feather and 3.5-inch TFT FeatherWing capacitive touch display. The calculator consists of a 10-digit LED-like display backed-up with 20-digit internal calculation precision.

This emulation reproduces the HP-35 calculator's v2.0 firmware where the change sign (CHS) key is active only after digit entry has begun. And because of the udecimal and utrig classes, calculation accuracy of monadic, dyadic, and trigonometric functions was improved. As an added bonus not present on the original calculator, a status message will appear just below the primary display when a calculation error is encountered.

The calculator's graphical layout was designed to mimic the aspect ratio of the original calculator -- that's why the left and right sides of the display screen were left empty. However, to provide a more reliable touch screen experience, the keys are somewhat proportionally larger than the original.

This project was inspired by Jeff Epler's DIY Desktop Calculator with CircuitPython project and Jeff's work to create CircuitPython versions of udecimal and utrig. Thank you Jeff!

GitHub Repository: https://github.com/CedarGroveStudios/CG-35_Calculator

Primary Code Module

The primary code module cg_35_calculator.py, imported by code.py, instantiates the display, plots the calculator case and buttons, and implements all calculator operational processes. This module uses a state machine design with the following named states:

• IDLE -- Display results or wait for input
• C_ENTRY -- Coefficient entry (keys: 0-9, ., CHS, EEX)
• E_ENTRY -- Exponent entry (keys: 0-9, ., CHS)
• STACK -- Stack management (keys: ENTER, CLR, CLX, STO, RCL, R, x<>y, π)
• MONADIC -- Monadic calculator functions (keys: LOG, LN, e^x, √x, ARC, SIN, COS,TAN, 1/x)
• DYADIC -- Dyadic calculator functions (keys: x^y, -, +, *, ÷)
• ERROR -- Calculation error

The calculator's display precision and internal calculation precision are specified using the variables DISPLAY_PRECISION and INTERNAL_PRECISION. Although the internal precision exceeds that of the original HP-35 calculator, it is recommended to keep the existing default settings of 10 digits and 20 digits, respectively, to avoid rounding errors.

The variable DEBUG can be use to provide additional internal register status via the REPL. This boolean variable defaults to False (no additional register status).

 

Basic premise:      Add lights (speed / noise / air-purity indicators, or needless dotstar+neopixel love), use small board to receive tachometer input and drive 24V fan PWM signal from particle sensor, along with new inputs for noise level.   Plus show off Blockly based programming on Adafruit IO, and update as and when the new maths functions become available, but for now write a quick CircuitPython version that illustrates all the desired functionality (to port to Adafruit IO).

Semi-finished code: - Functionally capable but no reactive light use, rainbow:
[Reproduced from https://github.com/tyeth/Ikea_ItsyBitsyEsp32_Air_Purifier/ ]

Wippersnapper

For those not in the know, WipperSnapper is Adafruit's plug-and-play firmware, which runs on their IO (think IOT) platform, offering free* data history(feeds) with graphs, dashboards, and automatic actions/triggers (along with integrating with other platforms like IFTTT). There is a paid upgrade for longer history, unlimited devices, SMS alerts, etc.

I love it because it's super quick and easy to test a sensor works, and to just get some data recording quickly. 

Goto a web-page, flash over usb, add sensors via control panel (feeds + graphs are automatic), done.

Under the hood it's an arduino sketch, so adding additional sensors via github pull requests is surprisingly easy (I've added a few because it makes my future tasks easier).

For this project I'm testing the Sensirion SEN55, which senses Nitrous Oxides (NOx), Volatile Organic Compounds (VOCs), with temperature and relative humidty as a reference (uses SGP40/41 inside), and measures particle counts at <1.0 micron, <2.5, <4.0, and <10.0 micron. The other models of this sensor have less features (SEN54: no NOx, SEN50: no NOx/VOC/Relative Humidity+Temp - only Particulate Counts).

From the standard drivers(arduino/Pi) created by Sensirion we can retrieve the typical particle size, along with the raw particle counts (or in SI units ug/m3), the temperature and humidity, and then two indexes for NOx and VOC. 
The NOx index has a baseline of 1.0, and if you hide the sensor under an upside down saucepan and use a lighter under the saucepan before sealing it back up then you will see a rise in the NOx index and then a return to baseline (1).
The VOC index is instead based at 100. You can detect VOC events from many things, the human breath can even be a source. I tested mine with a jar of clear nail varnish, but anything which you can smell, or smells chemically, is probably going to affect the sensor.

Connectivity-wise, it uses I2C, or other methods (UART?) which are as yet unpublished. The connector requires a JST-GHR 1.25mm 6 Pin compatible cable. The development kits include such a cable, but are heavily marked up cost-wise, like an additional 150% (£50 for kit, £20 for bare sensor). I advise getting a bare version with an additional cable from elsewhere (coolcomponents have a cable under £2). There is also a Grove connector version from seeedstudio.

Overview

Welcome to the Adafruit guide on creating a stunning Badger Mountain themed art piece! In this guide, we'll show you how to bring your artistic vision to life using the powerful Feather RP2040 microcontroller, along with an array of components including audio jacks, buttons, and LED strips.

Circuit Diagram

This article is for Circuit Python developers that use PIP and CircuitPython-Stubs in a Windows environment. 

Stubs are helpers for code completion hints with IDE's such as PyCharm, VSCode, and others.

Unfortunately PIP & CircuitPython-Stubs do not automatically stay updated.  These are things you must manually update when a new version of Circuit Python is released or whenever your heart dictates you want to update it.  This is a problem because I never remember to keep them updated and recently found out my version of stubs was last updated in Circuit Python 7.3.3 (we're now at Circuit Python 9.0.1). 

This is assuming you already have PIP and CircuitPython stubs installed.

The manual way to update them is:

python -m pip install --upgrade pip

pip install circuitpython-stubs --upgrade

These are the types of things I do not want to be required to remember to update.  I consider these things minutia that should automatically stay updated.

Windows Task Scheduler can automate the process of keeping both PIP and circuitpython-stubs up to date every time you log into Windows.  First we need to create a batch script and put it in a directory/folder that will always be available to Windows. 

I chose to put it in the following folder:

\Downloads\CircuitPython-Stubs_Updater

You can name the script whatever you'd like.  You can edit a .bat file as easly as a .txt file, you don't need a special IDE to do it, Notepad works fine for it.

I named my batch file:

circuitpython-stubs.bat

It resides inside of the CircuitPython-Stubs_Updater folder and includes the following code in the .bat file.

Introduction

Astronomy is my primary hobby and taking photographs of night-sky objects is my particular interest.  A downside to this hobby is that it is very weather dependent.  If it’s cloudy nothing can be seen.  Weather reports are important to monitor but they just serve the general area.  The sky conditions at my specific location are better monitored with an AllSky Camera.

An AllSky Camera is simply a camera with a fisheye lens that’s pointed up into the sky.  A program takes pictures of the sky all night long so checking the sky conditions can be done by looking at the latest sky image.  Is it too cloudy to take images?  Are clouds starting to move in?  Just check the AllSky Camera!

The Issue with Dew

Unfortunately, the dome of the AllSky Camera is prone to have dew forming on it when the humidity gets high.  Once that happens, the Allsky images are totally unusable.  To combat dew, many AllSky Cameras have a dew heater built into them.  The heater in my camera is very simple:  Apply 12 VDC and the heater is on.  Remove the voltage and the heater is off.  This applies about 10 W of power to the heater, and it does get hot enough to keep dew from forming on the dome.  Sometimes it gets too hot.

If the humidity is moderate the 10 W of power is way more than needed to keep the dome clear.  An unwanted side effect of too much heat is that cameras don’t like it.  The hotter a camera gets the noisier, or grainer, its picture becomes.  This is especially apparent with long exposures and AllSky Cameras can take up to 60-second exposures under a dark sky!  The better solution is to vary the amount of power applied to the heater so that only enough is applied to keep dew from forming, and no more.

 

The goal of this project is to build a Python based handheld and battery powered scientific calculator the size of a cigarette box (well, pocket calculator). Scientific, as in "reasonable precision". Float32 (single precision) is certainly acceptable for a display precision of, say 6 or 7 digits, but the follow-up rounding errors are not - at least not for me. I experimented with Decimal math before but ended up having to fight memory constraints with jepler-udecimal (https://github.com/jepler/Jepler_CircuitPython_udecimal) and my own extensions even on a Feather RP2040 with 256kB of user RAM. So I eventually decided to make a custom CircuitPython build and try to enable float64 (double precision) math. (Thanks to the Adafruit folks for their help!). Needless to say that float64 is entirely handled in C without the help of a potential floating-point unit (FPU) but then this approach is still much more CPU and memory efficient than implementing everything in Python.

The code for this project is on https://github.com/h-milz/circuitpython-calculator/ and will be discussed in this article.

The terminal window displays a couple of features of this tiny machine, from top to bottom: calculating pi using arctan(1), the arsinh of a complex argument, multiplying two numbers with uncertainties, and multiplying two fractions including reducing it to lowest (positive) denominator.

The dongle on the lower right is a PCF8523 RTC hanging off the Keyboard Featherwing's STEMMA Qt connector (which, sadly, is unusable if you want a handheld with a back cover ... What did arturo182 think?)

On the backside you can see the Adafruit Feather M4 Express and the LiPo battery, which is fixed to the Featherwing using a double-sided adhesive foam strip.