Metadata-Version: 2.1
Name: musiclang
Version: 0.8.12
Summary: A python package for music notation and generation
Home-page: UNKNOWN
Author: Florian GARDIN
Author-email: fgardin.pro@gmail.com
License: UNKNOWN
Project-URL: Documentation, https://musiclang.readthedocs.io/en/latest/
Project-URL: Source, https://github.com/MusicLang/musiclang/
Project-URL: Tracker, https://github.com/MusicLang/musiclang/issues
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: lxml (==4.9.1)
Requires-Dist: mido (==1.2.10)
Requires-Dist: music21 (==8.1.0)
Requires-Dist: numpy
Requires-Dist: pandas (==1.5.3)
Requires-Dist: scikit-learn (==1.1.3)
Requires-Dist: scipy (==1.9.3)
Requires-Dist: tensorflow
Requires-Dist: toml (==0.10.2)
Requires-Dist: tomli (==2.0.1)
Requires-Dist: xmlschema (==2.1.1)
Requires-Dist: transformers (==4.26.1)
Requires-Dist: tokenizers (==0.13.2)
Requires-Dist: partitura (==1.2.1)
Requires-Dist: torch

Musiclang
=========

![MusicLang logo](https://github.com/MusicLang/musiclang/blob/main/documentation/images/MusicLang.png?raw=true "MusicLang")


[![Documentation Status](https://readthedocs.org/projects/musiclang/badge/?version=latest)](https://musiclang.readthedocs.io/en/latest/?badge=latest)

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)](https://huggingface.co/floriangardin/musiclang)  to predict what could happen next in a musical score.
This framework is well suited to :
- Generate musical ideas quickly.
- Predict what could happen next in an existing midi file
- Create an interpretable and information rich text representation of a midi file

[Read our documentation](https://musiclang.readthedocs.io/en/latest).


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 :

```python
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')
```

2. Create, transform and harmonize a theme quickly : 

```python
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 !
```
![Happy birthday score](https://github.com/MusicLang/musiclang/blob/main/documentation/images/happy_birthday.png?raw=true "Happy Birthday")


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

```python
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=4, 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](mailto:fgardin.pro@gmail.com)


4. Mix everything together to create a new pieces of music !



