The Piscale is a bridge between Timescale and SonicPi.

The aspiration of this application is to create an approachable interface to allow developers/musicians and any data enthusiasts to create music from data.

The bridge here is starting with Timescaledb and Raspiberry PI, but I hope it inspires people to build more plugins and allow to mix different data into the same interface.

My genuine intuition to create this program is that I want to pipe data to sound synthesizers like the BPM represents the time of the music, the timeseries data can correlate and make noise driven by the data inputs.

Think about car issues in the motor, the owner of the car can detect if something is going wrong even not being an expert. And the mechanic can recognize several issues depending the noise of the motor.

My invite here is to put our data to make noise. To extract sound and meaning out of it.

The actual library is only loading a SonicPI client that can stream messages to the server using the data from Timescale. It will work with any Postgresql database, but I'm using Timescaledb directly to inherit all hypertable scenarios available for timeseries data. I also added the toolkit to allow to query more advanced statistics with the hyperfunctions and encourage me to explore new scenarios of data with statistics to drive the music.

I'm very open for ideas and I'd love to brainstorm about how to make this project something useful and available to researchers and sonification enthusiasts to join me on this journey. Please, use the discussions to bring new ideas or start new features.

The core lib will contain the minimal core to only offer the basic engines to use both Postgres and SonicPi.

It will be able to process multiple queries and pipe the data back to multiple backends. Allowing the user to orchestrate multiple instruments and scenarios, enabling the Data DJ to combine different queries configured as instruments.

One important aspect to fast prototype a new data sonification is make it easy to the enduser to express what they want.

Here are a few ideas to be implementing as part of the core library:

use_bpm Model.avg(:value).to_i

Use bin/console to start the application and confirm that you can listen to the application.

Paste the following code into your SonicPI app:

live_loop :tsdb do
  msg = sync("/osc:127.0.0.1:51062/run-code").last
  eval(msg)
end

It will just allow you to connect as a remote source into your Sonic PI and execute commands.

Make sure you adapt the port and url as the Cues view shows.

Want to learn more? Check out my sonification workshop

Use bin/console with a Postgresql URI to fetch data from the database. It expects you're using hypertables and it's already mapping all hypertables as models in the console.

After checking out the repo, run bin/setup to install dependencies. Then, run rake spec to run the tests. You can also run bin/console for an interactive prompt that will allow you to experiment.

To install this gem onto your local machine, run bundle exec rake install. To release a new version, update the version number in version.rb, and then run bundle exec rake release, which will create a git tag for the version, push git commits and tags, and push the .gem file to rubygems.org.

Bug reports and pull requests are welcome on GitHub at https://github.com/jonatas/piscale. This project is intended to be a safe, welcoming space for collaboration, and contributors are expected to adhere to the code of conduct.

The gem is available as open source under the terms of the MIT License.

Everyone interacting in the Piscale project's codebases, issue trackers, chat rooms and mailing lists is expected to follow the code of conduct.