Skip to main content

A python package for music notation and generation

Project description

Musiclang

MusicLang logo

Documentation Status

The Python framework to write, analyze, transform and predict music.

What is MusicLang ?

MusicLang which simply stands for "music language" is a Python framework implementing a new language for tonal music. This language allows composers to load, write, transform and predict symbolic music in a simple, condensed and high level manner.

MusicLang internally uses a LLM (Large Language Model) to predict what could happen next in a musical score. /!\ Please note that : we decoupled AI from the language itself in a new package called musiclang_predict. If you want to use AI capabilities of musiclang please install musiclang_predict package.

This framework is well suited to :

  • Generate musical ideas quickly.
  • Do symbolic music prediction or inpainting.
  • Create an interpretable and rich text representation of a midi file

Read our documentation.

How to install

MusicLang is available on Pypi :

pip install musiclang

Examples

  1. 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 (First degree of C major scale)
score = (I % I.M)(piano=[s0, s2, s4])

# Store it to midi
score.to_midi('c_major.mid')
  1. 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
score = score.get_counterpoint(fixed_parts=['violin__0'])

# Save it to musicxml
score.to_musicxml('happy_birthday.musicxml', signature=(3, 4), title='Happy birthday !')

# Et voilà !

Happy birthday score

  1. Predict a score using a deep learning model trained on musiclang language :

See MusicLang Predict for more information.

Contact us

If you want to help shape the future of open source music generation / language modeling, please contact us

License

The MusicLang base language (this package) is licensed under the BSD 3-Clause License. The MusicLang predict package and its associated models is licensed under the GPL-3.0 License.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

musiclang-0.26.0.tar.gz (182.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

musiclang-0.26.0-py3-none-any.whl (231.5 kB view details)

Uploaded Python 3

File details

Details for the file musiclang-0.26.0.tar.gz.

File metadata

  • Download URL: musiclang-0.26.0.tar.gz
  • Upload date:
  • Size: 182.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.8.18

File hashes

Hashes for musiclang-0.26.0.tar.gz
Algorithm Hash digest
SHA256 e7e6a9b84d6070ff24865ddc5b2190128f84808f349629fa4a4ba5dedbb48855
MD5 d64cbe7a2a32a7f1067d45b263647d72
BLAKE2b-256 eb4e6cc40782a3a06137cd0524c0d62f1437552cd6ff4b86465416ea07ffdd97

See more details on using hashes here.

File details

Details for the file musiclang-0.26.0-py3-none-any.whl.

File metadata

  • Download URL: musiclang-0.26.0-py3-none-any.whl
  • Upload date:
  • Size: 231.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.8.18

File hashes

Hashes for musiclang-0.26.0-py3-none-any.whl
Algorithm Hash digest
SHA256 998894ed0f3268112eaa008d3f31053033dd0f60ef0a573e8ad6ac3c2fd7cada
MD5 67e4652e8871f4252a2a3d772aee0a0e
BLAKE2b-256 7bb4fdc2a4c5b093af3956679150aba31b33803cb75390949152de385cd96ade

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page