A CircuitPython library for Fast Fourier Transforms (FFT) #CircuitPython #FFT @tdsepsilon

Tom posts on Twitter about creating a Fast Fourier Transform (FFT) library for CircuitPython!

The guide post has all the details:

I have been playing with the Adafruit CircuitPython for a while now on the PyGamer board . Using the Adafruit libraries to light up the NeoPixels and to display pictures and text on the screen.

Then I learned that the Hackaday Supercon attendees would be given an Adafruit Edge Badge along with the official badge. This had a built in microphone which sparked my interest on creating an audio spectrum waterfall plot of the measured frequency.

This was a bit of a problem because the library that python uses to perform the Fast Fourier Transform (FFT) did not have a CircuitPython port. So I decided to write my own code in CircuitPython to compute the FFT. Now I could have written C code to run underneath, but I have not gotten to that point yet, and also wanted to get this done for Supercon, which required a few other parts, so that drove my decision to just use pure Python.

Tom concludes:

I have really enjoyed using CircuitPython, as it is a much simpler method to playing with microcontrollers than Arduino. The ecosystem that Adafruit has developed makes it a breeze for developers, new and old, to quickly get a project off the ground and running. I hope more boards and manufactures make CircuitPython an option on their products as it provides fast visual feedback and is a simple way to work with microcontroller hardware. I also hope more people start creating libraries for the ecosystem so that future users have an easier time developing new creative things.

See the GitHub repo for the library here and the blog post here. Excellent work!

Learn more about CircuitPython at circuitpython.org and see the Adafruit Edge Badge here.

As 2022 starts, let’s take some time to share our goals for CircuitPython in 2022. Just like past years (full summary 2019, 2020, and 2021), we’d like everyone in the CircuitPython community to contribute by posting their thoughts to some public place on the Internet. Here are a few ways to post: a video on YouTub, a post on the CircuitPython forum, a blog post on your site, a series of Tweets, a Gist on GitHub. We want to hear from you. When you post, please add #CircuitPython2022 and email circuitpython2022@adafruit.com to let us know about your post so we can blog it up here.

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