Inspirations behind the project¶
This writing serves as documentation for the project roots. It also should be taken as a place to find artistic inspiration and general resources.
Modular workflow inspirations
One of the biggest inspirations for py-modular has been the eurorack environment. I started building eurorack modules a few months before I started developing this project. The concept of large ideas being broken down into small micro-processes that are each only concerned with a simple task is very helpful, and I think a more natural way of thinking. It is easy to get overwhelmed with complex synthesizers, whether they be software or hardware. It is more manageable to think only about sections of a synthesizer individually, like the oscillator, the filter, and the mixer.
In addition to the concept of eurorack and modular synthesis, I was heavily inspired by Max/MSP and Pure Data. Both of these, for those of you who don’t know, are visual programming environments for music and visuals. I enjoy a lot using Max/MSP, because it helps me to break down my own creative process, but it can be a bit tedious dragging “cables” between nodes constantly. As someone who is far more proficient with a keyboard than a mouse, I wanted something text based instead.
Another big inspiration for me was the open source Ossia Score. Ossia Score is a sequencer/DAW that focuses on a non-linear workspace. Using Ossia Score, I realized how much more creative potential there is when you break away from a traditional timeline workflow.
Generative music inspiration
A large part of this project has been trying to experiment and get to know AI technologies for creative purposes. The Magenta project was a large inspiration for me, as it is one of the few already well-established projects of the sort. I think that AI has a large potential with generative music techniques, and I wanted to explore this more. Magenta provides an incredible framework for working with these technologies, even for someone like myself with little experience. I wanted to try and build on this and see how their code base could be integrated into more traditional synthesis techniques, which was the starting point for the Nsynth grain cloud generator.
Another inspiration for the project and the generative aspects of the project, were creations like Endel, Dadabots, and Jukebox. These are algorithms that generate entire songs, or constantly flowing music. I think the concept of abstracting composition, and writing an algorithm instead of a score, is interesting and unexplored by most creatives.
The resources page also contains a list of reference and resources used during the development of py-modular. I strongly recommend reading it over if you want to learn something new.