Pippi: Computer Music With Python
v2.0.0 - Beta 4 (In Development)
Source code: https://github.com/luvsound/pippi
What is this?
Pippi is a library of computer music modules for python.
It includes a few handy data structures for music like
Wavetable, which are operator-overloaded
to make working with sounds and control structures simpler.
It also includes a lot of useful methods for doing common and not-so-common transformations to sounds and control structures.
from pippi import dsp sound1 = dsp.read('sound1.wav') sound2 = dsp.read('sound2.flac') # Mix two sounds both = sound1 & sound2 # Apply a skewed hann Wavetable as an envelope to a sound enveloped = sound * dsp.win('hann').skewed(0.6) # Or just a sine envelope via a shortcut method on the `SoundBuffer` enveloped = sound.env('sine') # Synthesize a 10 second graincloud from the sound, # with grain length modulating between 20ms and 2s # over a triangle shaped curve. cloudy = enveloped.cloud(10, grainlength=dsp.win('tri', dsp.MS*20, 2))
It comes with several oscs:
Alias- a highly aliased pulse train osc
Bar- a bar physical model (from Soundpipe)
Drunk- does a drunk walk on the y axis over a fixed set of random points w/hermite interpolation for smooth waveshapes (kind of like dynamic stochastic synthesis in one dimension)
DSS- a basic implementation of dynamic stochastic synthesis that does a drunk walk in two dimensions over a random set of breakpoints
FM- a basic two operator FM synth w/harmonicity ratio & modulation index controls
Fold- an infinite folding wavetable osc
Osc- an everyday wavetable osc
Osc2d- a 2d morphing wavetable osc
Pluck- a plucked string physical model (adapted from JOS)
Pulsar- a pulsar synthesis engine
Pulsar2d- a 2d morphing pulsar synthesis engine (pairs well with a stack of wavetables extracted with the
SineOsc- a simple sinewave osc (doesn't use wavetables)
Tukey- a tukey-window-based osc with waveshape modulation between square-like and sine-like
And many built-in effects and transformations:
- Easy independent control over pitch and speed for any
- Several forms of waveshaping and distortion including a crossover distortion ported from supercollider
- Sweapable highpass, lowpass, bandpass and band reject butterworth filters from Soundpipe
- Lots more!
As well as support for pitch and harmony transformations and non-standard tuning systems
from pippi import tune # Get a list of frequencies from a list of scale degrees frequencies = tune.degrees([1,3,5,9], octave=3, root='a', scale=tune.MINOR, ratios=tune.JUST) # Get a list of frequencies from a chord symbol using a tuning system devised by Terry Riley frequencies = tune.chord('ii69', key='g#', octave=5, ratios=tune.TERRY) # Convert MIDI note to frequency freq = tune.mtof(60) # Convert frequency to MIDI note note = tune.ftom(440.0) # Convert a pitch to a frequency freq = tune.ntf('C#3')
And basic graphing functionality for any
Wavetable -- some dumb examples pictured in the banner above.
from pippi import dsp sound = dsp.read('sound.wav') # Render an image of this sound's waveform sound.graph('mysound.png') # Render an image of a sinc wavetable with a label and scaled range dsp.win('sinc').graph('sinc.png', label='A sinc wavetable', y=(-.25, 1))
As well as other neat stuff like soundfont rendering support via tinysf!
from pippi import dsp, soundfont # Play a piano sound from a soundfont with general MIDI support (program change is zero-indexed) tada = soundfont.play('my-cool-soundfont.sf2', length=30, freq=345.9, amp=0.5, voice=0) # Save copy to your hard disk tada.write('tada.wav')
There are annotated example scripts in the tutorials directory which introduce some of pippi's functionality.
Beyond arriving at a good-enough stable API for the 2.x series of releases (and fixing bugs), my goal during the beta phase of development is to deal with the lack of documentation for this project.
Pippi requires python 3.6+ which can be found here:
The 3.5.x branch of python might work too, but is untested.
raspbian buster users: you must install the
aptto build the latest version of numpy.
To install pippi:
- Clone this repository locally:
git clone https://github.com/luvsound/pippi.git
- (Optional but recommended) Create a virtualenv somewhere where you want to work:
cd /my/pippi/projects; python3 -m venv venv; source venv/bin/activate
- (With your virtualenv active) Go back to the pippi source directory
cd /path/to/pippiand run
The final command does a few things:
- Installs python deps, so make sure you're inside a virtual environment if you want to be!
- Sets up git submodules for external libs
- Builds and installs Soundpipe
- Builds and installs pippi & cython extensions
Please let me know if you run into problems!
At the moment the best place to get pippi is using the method described above. Because of some packaging issues that need to be worked out, the version on pypi is quite a bit older and does not include most of the fun stuff.
To run tests
In many cases, this will produce a soundfile in the
tests/renders directory for the corresponding test. (Ear-driven regression testing...)
During the beta I like to keep failing tests in the main repo, so... most tests will be passing but if they all are passing, probably you are living in the future and are looking at the first stable release.
There are also shortcuts to run only certain groups of tests, like
test-wavesets -- check out the
Makefile for a list of them all.
While hacking on pippi itself, running
make build will recompile the cython extensions.
If you need to build sources from a clean slate (sometimes updates to
pxd files require this) then run
make clean build instead.
Project Nayuki for a compact FFT! (Used in
Paul Batchelor for all the goodness in Soundpipe that has made its way into Pippi. (See the
Bernhard Schelling for his TinySoundFont library used in the
Nando Florestan for his small public domain GM soundfont used in the test suite.
Pixeldroid for their OFL licensed console font used for labeling graphs.
@firstname.lastname@example.org for introducing me to the modulation param on tukey windows
James McCartney for his implementation of hermite interpolation used in the
Wavetable module and elsewhere.
Starling Labs for their zener diode softclip simulation and state variable filter implementation available in the
Jatin Chowdhury for their lovely sounding saturating feedback wavefolder.