livecoding

Python module to integrate tidalcycles and p5 using python-osc for creating audiovisual performances.

Installation

Just download this repository in root folder and import as a python module. On linux one can download with git with:

   git clone https://github.com/RafaelGoncalves8/livecoding

Configuration

In bootTidal.hs change this line from:

tidal <- startTidal (superdirtTarget {oLatency = 0.1, oAddress = "127.0.0.1", oPort = 57120}) (defaultConfig {cFrameTimespan = 1/20})

to:

:{
let prosTarget =
      Target {oName = "processing",
              oAddress = "127.0.0.1",
              oPort = 7070,
              oLatency = 0.2,
              oSchedule = Live,
              oWindow = Nothing
             }
:}


:{
tidal <- startStream defaultConfig [(superdirtTarget, [superdirtShape]),
                                (prosTarget, [superdirtShape])
                               ]
:}

Then every OSC data sent to Super Dirt is also sent to port 7070 (which the module uses as default for receiving tidal data).

Example

from livecoding import TidalSession
from p5 import *

class MyLiveCodingSession(TidalSession):

    def setup(self):
        size(640, 360)
        background(255)

    def draw(self):
        with self.lock:
            if self.parameters['s'] == 'bd':
                background(255, 50, 50)
            elif self.parameters['s'] == 'sn':
                background(50, 50, 255)

lc = MyLiveCodingSession()
lc.run()

In this example, one creates a session by inheriting a class from TidalSession and writing the functions for setup and draw as one would using p5. The variable self.lock is a threading.Lock used for avoiding race condition. The variable self.parameters is a dictionary in which each key is an OSC variable name and each value is its current value.