sc3nb

sc3nb is a python package that offers an interface to SuperCollider3 (SC3), with special support to be used within jupyter notebooks.

• Documentation
• Source code
• Bug reports

The goal of sc3nb is to facilitate the development of auditory displays and interactive sonifications by teaming up

• python (and particularly numpy, scipy, pandas, matplotlib etc.) for data science
• and SuperCollider3 for interactive real-time sound rendering. ​

It allows:

• to interface with the SuperCollider audio server (scsynth) aswell as the SuperCollider Language and Interpreter (sclang) via the SC class
• The SuperCollider audio server can be started and addressed via
  • OSC directly with OSC messages and bundles
  • Python implementations of Classes from SuperCollider like Synth, SynthDef, Buffer and Bus
  • the Score class for non-realtime synthesis
• use the SuperCollider language (sclang) interactively via a subprocess.
  • write SuperCollider language code in Jupyter Notebooks and let sclang evaluate it.
  • inject Python variables into your sclang code
  • get the results of the sclang code in Python
• helper functions such as linlin, cpsmidi, midicps, clip, ampdb, dbamp which work like their SC3 counterparts.

sc3nb can be used for

• multi-channel audio processing
• auditory display and sonification
• sound synthesis experiment
• audio applications in general such as games or GUI-enhancements
• signal analysis and plotting
• computer music and just-in-time music control
• any usecase that the SuperCollider 3 language supports

It is meant to grow into a backend for a sonification package, and can be used both from jupyter and in standard python software development.

Installation

• To use sc3nb you need a installation of SuperCollider on your system. See SuperCollider Download for installation files.
• To install sc3nb you can
  • install it locally in editable mode (i.e. changes to sc3nb code will automatically be "re-installed").
  • clone the repository from https://github.com/interactive-sonification/sc3nb
  • from inside the sc3nb directory run pip install -e .
  • or install it directly from PyPI using pip install sc3nb

Examples

We provide examples in the form of Jupyter notebooks. You see them executed in the User Guide section of the documentation and also download them from the sc3nb examples folder.

Publications & Citation

• A paper introducing sc3nb can be found at https://doi.org/10.1145/3478384.3478401
• The belonging supplementary material can be found at https://doi.org/10.4119/unibi/2956379
• The presentation of the paper can be found at https://www.youtube.com/watch?v=kuZZSNCS53E

If you use sc3nb please cite the sc3nb introduction paper https://doi.org/10.1145/3478384.3478401