A python package for music notation and generation
Project description
Musiclang
The Python framework to write, analyze, transform and predict music.
What is MusicLang ?
MusicLang which simply stands for "music language" is a Python framework that allows composers to write symbolic music in a condensed and high level manner. It can be used to write, arrange, transform or predict new music. This framework is not only another notation software but also an assistant that is able to automate some tasks that would normally be tedious for a composer. It is naturally good at analyzing and manipulating existing pieces of music in musicxml or midi format.
How to install
MusicLang is available on Pypi :
pip install musiclang
Or use this repo for the latest version :
pip install git+https://github.com/MusicLang/musiclang
Examples
- A hello world example to create a C-major chord in musiclang and save it to midi :
from musiclang.library import *
# Write A C major chord
score = (I % I.M)(piano=[s0, s2, s4])
# Store it to midi
score.to_midi('c_major.mid')
- Create, transform and harmonize a theme quickly :
from musiclang.library import *
# Create a cool melody (the beginning of happy birthday, independant of any harmonic context)
melody = s4.ed + s4.s + s5 + s4 + s0.o(1) + s6.h
# Create a simple accompaniment with a cello and a oboe
acc_melody = r + s0.o(-1).q * 3 + s0.o(-1).h
accomp = {'cello__0': acc_melody, 'oboe__0': acc_melody.o(1)}
# Play it in F-major
score = (I % IV.M)(violin__0=melody, **accomp)
# Repeat the score a second time in F-minor and forte
score += (score % I.m).f
# Just to create an anachrusis at the first bar
score = (I % I.M)(violin__0=r.h) + score
# Transform a bit the accompaniment by applying counterpoint rules automatically
from musiclang.transform.library import create_counterpoint_on_score
score = create_counterpoint_on_score(score, fixed_parts=['violin__0'])
# Save it to musicxml
score.to_musicxml('happy_birthday.musicxml', signature=(3, 4), title='Happy birthday !')
# Et voilà !
- Predict a score using a deep learning model trained on musiclang language :
from musiclang.library import *
from musiclang import Score
# Some random bar of chopin op18 Waltz
score = ((V % III.b.M)(
piano__0=s0 + s2.e.mp + s3.e.mp,
piano__4=s0.e.o(-2).p + r.e + s0.ed.o(-1).mp + r.s,
piano__5=r + s4.ed.o(-1).mp + r.s,
piano__6=r + s6.ed.o(-1).mp + r.s)+
(V['7'] % III.b.M)(
piano__0=s2.ed.mp + r.s,
piano__2=s4.ed.mp + r.s,
piano__4=s6.ed.o(-1).mp + r.s,
piano__5=s0.ed.o(-1).mp + r.s,
piano__6=s4.ed.o(-1).mp + r.s))
# Predict the next two chords of the score using huggingface musiclang model
predicted_score = score.predict_score(n_chords=2, temperature=0.5)
# Save it to midi
predicted_score.to_midi('test.mid')
Please note that this feature is still experimental, it will only work with piano music for now and the model is not yet trained on a large corpus of music. If you want to help us train a better model, please contact us
- Mix everything together to create a new pieces of music !
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