Metadata-Version: 2.1
Name: musiclang
Version: 0.8.10
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: 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
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.

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


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
---------

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=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](mailto:fgardin.pro@gmail.com)


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



