sciss / patterns   1.11.0

GNU Affero General Public License v3.0 GitHub

A pattern library for Scala and SoundProcesses, inspired by SuperCollider's. Mirror of

Scala versions: 3.x 2.13 2.12 2.11
Scala.js versions: 1.x


Build Status Maven Central


Patterns is a library that brings SuperCollider style patterns to Scala, and ultimately to SoundProcesses. Patterns are descriptions of streams, streams are stateful iterators, here implemented with an optional transactional layer.

This project is (C)opyright 2017–2022 by Hanns Holger Rutz. All rights reserved. This project is released under the GNU Affero General Public License v3+ and comes with absolutely no warranties. To contact the author, send an e-mail to contact at

requirements / installation

This project builds with against Scala 2.12, 2.13, Dotty (JVM), and Scala 2.13 (JS). The last version to support Scala 2.11 was 0.13.0.

To link to it:

libraryDependencies += "de.sciss" %% "patterns" % v

The current version v is "1.11.0".

There are two sub-modules which can be linked to separately:

  • patterns-core is the foundation, it works with the mutable (non-transactional) Base system
  • patterns-lucre adds support for Lucre type transactional systems (what is used in SoundProcesses)


Please see the file

getting started

Useful links:


import de.sciss.lucre.Plain
import de.sciss.patterns._, graph._

val g = Graph {
  Pat.loop(3) {
    Brown(1, 100, 3).take(4)

implicit val ctx: Context[Plain] = Context()
// e.g. List(45, 42, 43, 41,   88, 85, 88, 91,   19, 21, 21, 23)

Note the following things:

  • implicit conversions for using constants as patterns come from de.sciss.patterns._
  • all pattern classes (sub-classes of Pat) are defined in package de.sciss.patterns.graph
  • you should always wrap a pattern expression in a Graph { } block. This ensures that you can use control structures such as map and flatMap.
  • streams are implemented without co-routines; we provide some mechanism for commonly used imperative statements, such as loop and while; here we use Pat.loop(n) { } which can be understood as (0 until n).flatMap { ... }, i.e. it builds the inner pattern three times and concatenates the results.
  • because we have dedicated namespace, there is no P prefix in class-names, thus it is Brown and not Pbrown.
  • we treat patterns similar to Scala collections, so many of the same operations are defined, such as drop and take (corresponding with drop and keep in SuperCollider).
  • a pattern is expanded to a Stream using expand. That method takes an implicit context and transaction. Here we use a Plain context which does not use transactions. We make the context implicitly available, so expand works. If you are interested in persistent streams, have a look at the StreamSerializationSpec test source.
  • to get values from a stream, iterate using hasNext and next(), or call toIterator, toList and toVector.

For a more complex example, see the RonTuplePure test source code. For further questions, consult the source code, API docs (sbt doc).

notes for implementing new patterns

  • there should a Pat Element in graph
  • there should be a corresponding Stream Element in stream
  • there should be a unit test verifying correct production of values
  • there should be a unit test verifying correct reaction to reset
  • there should be a unit test verifying correct serialization

to-do / things to explore

  • stream caching in order to avoid excessive forks at the expansion. We would cache one or two elements, so that stuff such as a + a would only require a single a expansion of a (and of the inputs of a accordingly). This would hopefully speed things up a bit.
  • multi-channel-expansion, while principally supported, is not well tested, with respect to correctness and type-class / DSL support