GSoC/GCI Archive
Google Summer of Code 2013

Mixxx DJ Software

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Mixxx is the most popular free DJ software in the world. Mixxx began as one of the earliest MP3 DJ solutions and as a result has attracted millions of users worldwide. Our mission is to provide these users with a beautiful, intuitive DJ mixer with features that rival and lead proprietary commercial solutions such as Traktor, Serato, and Virtual DJ.

As a contributor to the Mixxx project you will:

  • Write code that is used by millions of professional DJs worldwide.
  • Learn the tricks of trade in cross-platform deployment -- your feature will ship to users on Windows, Mac OS X, and Linux.
  • Learn about how to write performance-optimized code where microseconds make a difference.
  • Work with a quirky team of hackers, DJs and artists.

Working on Mixxx is a great way to get involved in open-source, learn valuable skills that look great on a resume, and have a fun time doing it.


  • Mixxx Loop Recorder The Mixxx loop recorder will help DJs explore more creative possibilities in realtime using the Mixxx DJ software.
  • Non-Blocking Database Access I choosed one of avaiable projects at Mixxx’s ideas page -- “Non-Blocking Database Access”. I have experience in C++ and Qt programming (including programming of databases and threads). Also, I’m a little bit musician, so it is curious to become a part of creative developers team.
  • Perfect the MIDI Mapping Workflow: Support Searching Presets from API Engine Server Mixxx, a popular free cross-platform DJ mixing software, currently has some features need to design and develop and some bugs need to fix. My proposal is to perfect the preset mapping workflow, as well as develop an api server for users to get presets from or other websites. Expect these two major tasks, I will try to implement software update manager and enhance Language options. Then, a series of tests in different platforms shall be performed. Finally,Some translation tasks,technical documents and manual shall be developed.
  • Track Suggestions Based On Data, Set History, and Sonic Similarity Building upon earlier work on the track selector branch, I hope to offer an integrated solution that draws on publicly available data from the API, sonic features of the music (such as tempo, key, and timbre) and on the user's set history, creating a personally tailored set of suggestions for the next track.