contributor_docs/project_wrapups/junshern_gsoc_2018.md
My project this summer had the goal of making p5.js-sound a friendly platform for algorithmic music composition tasks.
In line with this objective, work for the project involved building up features, fixing bugs, adding documentation and producing examples of p5.js sketches related to algorithmic composition.
To encourage the use of these features and resources we've built for algorithmic composition, the project culminates in an online tutorial which walks through a number of examples and best practices for algorithmic composition on p5.js-sound.
Note that most contributions for this project are on the p5.js-sound repository, unless otherwise stated. Links should link to the correct issues and pull requests in any case.
All in all, it has been a highly satisfying summer. When we first started work, there were a lot of questions up in the air about the best way to go about implementing algorithmic music in p5.js-sound. Fortunately, we were able to build off the excellent work from past contributors (including work from previous GSoC participants!) to get all the functionality we needed.
At the end of this project, we can now confidently recommend p5.js-sound as a capable and reliable library for developing algorithmic music. The examples and final tutorial show these capabilities quite well, and hopefully the work done in this project will inspire and encourage many users to create their own algorithmic music applications!
Any questions pertaining to this project may be addressed via Issues on the p5.js-sound repository, or on the tutorial repository if directly related to tutorial content. Simply create a new Issue and either assign or tag me in the conversation with @junshern. For anything else, don't hesitate to get in touch at [email protected]!
Huge thanks goes to my mentor Jason Sigal for all his support and guidance throughout the project, as well as to all developers and community members of p5.js and the Processing Foundation who made all of this possible.
Thank you so much!