Play multiple sound files on multiple output devices with Python and sounddevice

Ever wanted to have multiple different sound files playing on different output devices attached to a host computer? Say you’re writing a DJing application where you want one mix for headphones and one for the speakers. Or you’re doing some sort of kiosk or art installation where you have many sets of speakers that need to all be playing their own sound file but the whole thing needs to be synchronized. This would even be cool for something like an escape room.

The ladder example is where I needed this bit of code. I’ve been working with interdisciplinary artist Sara Dittrich on a few projects recently and she asked if I could come up with a way to play 8 different mono sound files on 8 different loudspeakers. Here’s a video of the whole setup in action, and an explanation of the project:

I’ve wrapped up all of the code for the art installation project, and that can be found in a github repo here. It includes the startup functionality etc. If you’re interested in recreating the video above, that repo would be a good starting place. The following is a list of the parts used to make that build happen:

Multi-Audio Example

It is worth it to give a simple example of how to play multiple files on multiple audio devices using python. I couldn’t find an examples on how to do this online and had to spend some time experimenting to make it all come together. Hopefully this saves you the trouble.

To install sounddevice on my Raspberry Pi, I had to run the following commands:

For this example, let’s say there are 4 audio files in the same directory as multi.py , so the directory looks like this:

The code is based on the sounddevice library for python, whose documentation is pretty sparse. This script will find the audio files, and then play them on as many devices as there are attached. For example, if you have 3 sound devices it will play 1.wav, 2.wav and 3.wav on devices 1-3. If you have any questions, feel free to ask:

Here are some more photos of the build:

Why you should use Processes instead of Threads to isolate loads in Python

Key Learning

Python uses a Global Interpreter Lock to make sure that  memory shared between threads isn’t corrupted. This is a design choice of the language that has it’s pros and cons. One of these cons is that in multi-threaded applications where at least one  thread applies a large load to the CPU, all other threads will slow down as well.

For multi-threaded Python applications that are at least somewhat time-sensitive, you should use Processes over Threads.

Experiment

I wrote a simple python script to show this phenomenon. Let’s take a look.

The core is this increment function. It takes in a Value and then sets it over and over, increment each loop, until the running_flag is set to false. The value of count_value is what is graphed later on, and is the measure of how fast things are going.

The other important bit is the load function:

Like incrementload is the target of a thread or process. The z variable quickly becomes large and computing the loop becomes difficult quickly.

The rest of the code is just a way to have different combinations of increment and load running at the same time for varying amounts of time.

Result

The graph really tells the story. Without the load thread running, the process and thread versions of increment run at essentially the same rate. When the load thread is running, increment  in a thread grinds to a halt compared to the process which is unaffected.

That’s all! I’ve pasted the full source below so you can try the experiment yourself.

Raspberry Pi Digital Hourglass

Trying to get the most out of a day has been big theme of my life lately, as I’m sure it is for many people. I’ve found that I always manage my time better when things are urgent; I’m considerably more productive when I have to be.

I want an ascetically pleasing way to be able to represent how much time is left in the day at a granular scale, like an hourglass. Watching individual seconds disappear will look cool and (hopefully) create that sense of urgency that I want to induce.

Technically, this is a really simple thing to accomplish thanks to python and pygame. Here’s a video of a proof of concept running on my laptop:

At the start of each day, the display is filled with squares at random locations, with a random color. As each second elapses, a square will vanish.

To make it easier to see for the video, I’ve made the squares much bigger than they will actually be for the final build. This is what the display looks like with the squares at their actual size:

The code really really simple, like less than 100 lines simple. Here’s how it works:

Here’s the version of the code running on my computer in the video:

Let’s walk through some of the design decisions of this code. The first thing that’s worth talking about is how the data for the squares is handled:

It’s just an object with no methods, and on initialization, all the parameters of the square (location and color) are generated randomly as opposed to just floating the raw numbers in arrays around (even though that’s basically what is happening). This let’s us fill the squares array very easily later on in the file here:

and here:

When it comes time to draw these squares, it also makes that pretty intuitive:

Again, very simple stuff, but worth it to talk about.

I’ll be back at my place that has the Raspberry Pi and display I would like to use for this project, so more on this then.

Thanks for reading!

PiPlanter 2 | Solving Broken Pipe Errors [Errno 32] in Tweepy

If I haven’t mentioned it already, https://twitter.com/piplanter_bot IS the new twitter account for PiPlanter. Like last time, I’m using the tweepy library for python to handle all things twitter for the project. What I’m NOT using this time is Flickr. From a design point of view, it wasn’t worth it. It was too complicated and had too many things that could go wrong for me to continue using it. Twitter is more than capable of hosting images, and tweepy has a very simple method of passing these images to twitter. Recently I moved the whole setup indoors and mounted it all onto a shelf seen here and it came with a set of strange problems.

Long story short, what I think happened was that since I moved them to a different location, the complexity of the images increased, causing an increase in the size of the images themselves. A broken pipe error implies that the entirety of the package sent to twitter wasn’t sent, causing the tweet not to go through. I first started to suspect this problem after seeing this:

 

The graphs were going through just fine, but images were seeming to have a hard time. You can’t tell from this photo, but those tweets are hours apart as opposed to the 20 minutes they are supposed to be. Once I started having this problem, I bit the bullet and integrated logging into my project which produced this log:

Hours and hours of failed tweets due to “[Errno 32] Broken pipe”. I tried a lot of things, I figured out that it was the size of the images after seeing this:

Photos that were simple in nature had no problem being sent. After scaling the image size down, I’ve had absolutely no problem sending tweets.


If you are tweeting images with tweepy in python and getting intermediate Broken pipe errors, decrease the size of your image.
Thanks for reading.

Hey! This post was written a long time ago, but I'm leaving it up on the off-chance it may help someone, but proceed with caution. It may not be a good idea to blindly integrate this code or work into your project, but instead use it as a starting point.

PiPlanter | Bringing most of it together

Last night I finished the majority of the software for this project. Here’s a video of me going over what happened and what the program does in simpler terms:

Essentially, every hour, the raspberry pi samples data from 4 humidity probes, an LDR and a tmp sensor. Once the sampling is complete, it dumps the data into a mysql database. From there the data is rendered into a graph using pChart in the form of a .png image. From there, that .png files is uploaded to flickr using this api. Once the file is uploaded, it returns it’s photo ID to the python script. From there, a tweet is built containing the brightness at the time of the tweet, the temperature at the time of the tweet, and the average moisture of the plants. It also uses the photo ID from flickr obtained earlier to build a URL leading to that image on flickr which it tweets as well. The final part of the tweet is a url that leads to this post!

That was a lot of explanation, but this program does quite a bit. The source comes in two parts, here’s the python script that handles the brunt of the processing. You will need a bunch of libraries to run this, you could pick through past posts of mine to find what those are, but when I do a final post for this project I will include all of those.

Here’s the .php script that renders the graph from the mysql data. It is called by the python script.

Thanks for reading!

Hey! This post was written a long time ago, but I'm leaving it up on the off-chance it may help someone, but proceed with caution. It may not be a good idea to blindly integrate this code or work into your project, but instead use it as a starting point.