If there’s one thing that’s more fun than a comic, it’s a randomly generated comic. Well, perhaps that’s not true, but Reddit user [cadinb] wrote some software to generate a random comic strip and then built a robot case for it. Push a button on the robot and you’re presented with a randomly generated comic strip from the robot’s mouth.
The software that [cadinb] wrote is in Processing, an open source programming language and “sketchbook” for learning to code if you’re coming from a visual arts background. The Processing code determines how the images are cropped and placed and what kind of background they get. Each image is hand drawn by [cadinb] and has information associated with it so the code knows what the main focus of the image is. Once the panels are created, the final image is passed on to a thermal printer for printing. Everything is controlled from a Python script running on a Raspberry Pi and the code, strip artwork, and case is all available online to check out.
Now that the comic can print, a case is needed for the printer and controls. [cadinb] designed a case in Illustrator after creating a prototype out of foam core. The design was laser cut and then coloured – the main body with fabric dye and the arms stained with coffee!
It was only a matter of time. Everything else is getting its data logged and reported to the Internet for detailed analysis, so why should our rodents be any different? The cover story is that [Nicole Horward] hooked her pet hamster Harold up to the web because she wanted to see if he was getting as much exercise as he should. The real reason is, of course, that Harold wanted to show off to his “friends” on Hamsterbook.
The hardware side of this hack is very simple, a magnetic door sensor (like the kind used in alarm systems) is used to detect each time the wheel makes a complete rotation. The sensor is hooked up to the GPIO pins of a Raspberry Pi, where it’s read by a Python script. A small LCD screen was added to give some visual feedback on Harold’s daily activity, and the whole thing was boxed up in a laser cut enclosure.
That gave [Nicole] a cute little display next to Harold’s cage, but it didn’t do much for analyzing his activity. For that, a script is used to upload the data every minute to a ThingSpeak channel via MQTT. This automatically generates attractive graphs from the raw data, making it much easier to visualize what’s happening over the long term.
Pi-hole is an open source project to turn that Raspberry Pi collecting dust in your drawer into a whole-network ad blocking appliance. Not only does it stop ads from showing up on all your computers and mobile devices, it also keeps track of how many ads have been blocked and where they came from. Just in case you wanted to know how many thousands of ads you missed out on for a given time period.
While the graphs generated in the web interface of Pi-hole are slick and all, what if you just wanted a quick way of visualizing how effective your ad blocking system is? You’re not so much worried about the exact figures, you just want something to blink away on your desk and let you know all those ads are going to /dev/null. Enter the aptly named pi-hole-visualizer by [simianAstronaut].
With the addition of a Sense HAT to the Pi running the ad blocking, this Python script will generate an animated visualization that can be easily interpreted even from a distance. The primary display is a bar graph of DNS traffic, where the height and color of each column indicate relative activity within a specific time interval. A second screen shows a spiral graph which gives you an idea of what percentage of ads were blocked before they hit your devices.
An array of options can be given to the script from the command line; controlling both physical aspects of the display like orientation and LED brightness, as well the configurable parameters for the different available visualizations. As an added bonus, there’s also support for using the Sense HAT joystick to switch between modes interactively.
What does it take to build a quantum computer? Lots of exotic supercooled hardware. However, creating a simulator isn’t nearly as hard and can give you a lot of insight into how this kind of computing works. A simulator doesn’t even have to be complicated. Here’s one that exists in about 150 lines of Python code.
You might wonder what the value is. After all, there are plenty of well-done simulators including Quirk that we have looked at in the past. What’s charming about this simulator is that with only 150 lines of code, you can reasonably read the whole thing in a sitting and gain an understanding of how the different operations really affect the state.
In a previous post, I showed how you could upload images into a Discord server from Python; leveraging the popular chat platform to simplify things like remote monitoring and push notifications on mobile devices. As an example, I showed an automatically generated image containing the statistics for my Battlefield 1 platoon which gets pushed to member’s devices on a weekly basis.
The generation of that image was outside the scope of the original post, but I think it’s a technique worth discussing on its own. After all, they say that a picture is worth 1000 words. So that means a picture that actually contains words must be worth way more. Like, at least 2000, easy.
Being able to create images from your textual data can lend a bit of flair to your projects without the need to create an entire graphical user interface. By putting a text overlay on a pre-rendered image, you can pull off some very slick visuals with a minimum amount of system resources. So long as you have a way of displaying an image file, you’re good to go.
In this post I’ll quickly demonstrate how to load an image, overlay it with text, and then save the resulting image to a new file. This technique is ideal in situations where a display doesn’t need to be updated in real-time; visuals can be generated at regular intervals and simply displayed as static images. Possible uses include weather displays, “magic” mirrors, public signage, etc. Continue reading “Making Pictures Worth 1000 Words in Python”→
It is February of 2018. Do you remember what you were doing in December of 2012? If you’re [juppiter], you were starting your CNC Embroidery Machine which would not be completed for more than half of a decade. Results speak for themselves, but this may be the last time we see a first-generation Raspberry Pi without calling it retro.
The heart of the build is a vintage Borletti sewing machine, and if you like machinery porn, you’re going to enjoy the video after the break. The brains of the machine are an Arduino UNO filled with GRBL goodness and the Pi which is running CherryPy. For muscles, there are three Postep25 stepper drivers and corresponding NEMA 17 stepper motors.
The first two axes are for an X-Y table responsible for moving the fabric through the machine. The third axis is the flywheel. The rigidity of the fabric frame comes from its brass construction which may have been soldered at the kitchen table and supervised by a big orange cat. A rigid frame is the first ingredient in reliable results, but belt tension can’t be understated. His belt tensioning trick may not be new to you, but it was new to some of us. Italian translation may be necessary.
The skills brought together for this build were vast. There was structural soldering, part machining, a microcontroller, and motion control. The first time we heard from [juppiter] was December 2012, and it was the result of a Portable CNC Mill which likely had some influence on this creation. Between then, he also shared his quarter-gobbling arcade cabinet with us.
Discord is an IRC-like chat platform that all the young cool kids are hanging out on. Originally intended as a way to communicate during online games, Discord has grown to the point that there are servers out there for nearly any topic imaginable. One of the reasons for this phenomenal growth is how easy it is to create and moderate your own Discord server: just hit the “+” icon on the website or in the mobile application, and away you go.
As a long-time IRC guy, I was initially unimpressed with Discord. It seemed like the same kind of stuff we’ve had for decades, but with an admittedly slick UI. After having used it for a few months now and joining servers dedicated to everything from gaming to rocket science, I can’t say that my initial impression of Discord is inaccurate: it’s definitely just a modern IRC. But I’ve also come to the realization that I’m OK with that.
But this isn’t a review of Discord or an invitation to join the server I’ve setup for my Battlefield platoon. In this article we’re going to look at how easy it is to create a simple “bot” that you can plug into a Discord server and do useful work with. Since anyone can create a persistent Discord server for free, it’s an interesting platform to use for IoT monitoring and logging by simply sending messages into the server.