musicpy

中文

Have you ever thought about writing music with codes in a very concise, human-readable syntax?

Musicpy is a music programming language in Python designed to write music in very handy syntax through music theory and algorithms. It is easy to learn and write, easy to read, and incorporates a fully computerized music theory system.

Musicpy can do way more than just writing music. This package can also be used to analyze music through music theory logic, and you can design algorithms to explore the endless possibilities of music, all with musicpy.

With musicpy, you can express notes, chords, melodies, rhythms, volumes and other information of a piece of music with a very concise syntax. It can generate music through music theory logic and perform advanced music theory operations. You can easily output musicpy codes into MIDI file format, and you can also easily load any MIDI files and convert to musicpy's data structures to do a lot of advanced music theory operations. The syntax of musicpy is very concise and flexible, and it makes the codes written in musicpy very human-readable, and musicpy is fully compatible with python, which means you can write python codes to interact with musicpy. Because musicpy is involved with everything in music theory, I recommend using this package after learning at least some fundamentals of music theory so you can use musicpy more clearly and satisfiedly. On the other hand, you should be able to play around with them after having a look at the documentation I wrote if you are already familiar with music theory.

Documentation

See musicpy wiki or Read the Docs documentation for complete and detailed tutorials about syntax, data structures and usages of musicpy.

This wiki is updated frequently, since new functions and abilities are adding to musicpy regularly. The syntax and abilities of this wiki is synchronized with the latest released version of musicpy.

You can click here to download the entire wiki of musicpy I written in pdf and markdown format, which is updating continuously.

Installation

Make sure you have installed python (version >= 3.7) in your pc first. Run the following line in the terminal to install musicpy by pip.

pip install musicpy

If you need to read and write musicxml files, you can install the relevant dependencies by adding [musicxml] after the above command. If you need to use the raw module (musicpy.daw), you can install the relevant dependencies by adding [daw]. Like this:

pip install musicpy[musicxml]
pip install musicpy[daw]
pip install musicpy[daw, musicxml]

Note 1: On Linux, you need to make sure the installed pygame version is older than 2.0.3, otherwise the play function of musicpy won't work properly, this is due to an existing bug with newer versions of pygame. You can run pip install pygame==2.0.2 in terminal to install pygame 2.0.2 or any version that is older than 2.0.3. You also need to install freepats to make the play function works on Linux, you can run sudo apt-get install freepats (on Ubuntu).

Note 2: If you cannot hear any sound when running the play function, this is because some IDE won't wait till the pygame's playback ends, they will stops the whole process after all of the code are executed without waiting for the playback. You can set wait=True in the parameter of the play function, which will block the function till the playback ends, so you can hear the sounds.

Note 3: If you are using Linux or macOS, one of the dependency libraries of the daw module, sf2_loader, has some necessary configuration steps, you can refer to here for details.

In addition, I also wrote a musicpy editor for writing and compiling musicpy code more easily than regular python IDE with real-time automatic compilation and execution, there are some syntactic sugar and you can listen to the music generating from your musicpy code on the fly, it is more convenient and interactive. I strongly recommend to use this musicpy editor to write musicpy code. You can download this musicpy editor at the repository musicpy_editor, the preparation steps are in the README.

Musicpy is all compatible with Windows, macOS and Linux.

Musicpy now also supports reading and writing musicxml files, note that you need to install partitura to use the functionality by pip install partitura.

Importing

Place this line at the start of the files you want to have it used in.

from musicpy import *

or

import musicpy as mp

to avoid possible conflicts with the function names and variable names of other modules.

Composition Examples

Because musicpy has too many features to introduce, I will just give a simple example code of music programming in musicpy:

# a nylon string guitar plays broken chords on a chord progression

guitar = (C('CM7', 3, 1/4, 1/8)^2 |
          C('G7sus', 2, 1/4, 1/8)^2 |
          C('A7sus', 2, 1/4, 1/8)^2 |
          C('Em7', 2, 1/4, 1/8)^2 | 
          C('FM7', 2, 1/4, 1/8)^2 |
          C('CM7', 3, 1/4, 1/8)@1 |
          C('AbM7', 2, 1/4, 1/8)^2 |
          C('G7sus', 2, 1/4, 1/8)^2) * 2

play(guitar, bpm=100, instrument=25)

Click here to hear what this sounds like (Microsoft GS Wavetable Synth)

If you think this is too simple, musicpy could also produce music like this within 30 lines of code (could be even shorter if you don't care about readability). Anyway, this is just an example of a very short piece of electronic dance music, and not for complexity.

For more musicpy composition examples, please refer to the musicpy composition examples chapters in wiki.

Brief Introduction of Data Structures

note, chord, scale are the basic classes in musicpy that builds up the base of music programming, and there are way more musical classes in musicpy.

Because of musicpy's data structure design, the note class is congruent to integers, which means that it can be used as int directly.

The chord class is the set of notes, which means that it itself can be seen as a set of integers, a vector, or even a matrix (e.g. a set of chord progressions can be seen as a combination of multiple vectors, which results in a form of matrix with lines and columns indexed)

Because of that, note, chord and scale classes can all be arithmetically used in calculation, with examples of Linear Algebra and Discrete Mathmetics. It is also possible to write an algorithm following music theory logics using musicpy's data structure, or to perform experiments on music with the help of pure mathematics logics.

Many experimental music styles nowadays, like serialism, aleatoric music, postmodern music (like minimalist music), are theoretically possible to make upon the arithmetically performable data structures provided in musicpy. Of course musicpy can be used to write any kind of classical music, jazz, or pop music.

For more detailed descriptions of data structures of musicpy, please refer to wiki.

Summary

I started to develop musicpy in October 2019, currently musicpy has a complete set of music theory logic syntax, and there are many composing and arranging functions as well as advanced music theory logic operations. For details, please refer to the wiki. I will continue to update musicpy's video tutorials and wiki.

I'm working on musicpy continuously and updating musicpy very frequently, more and more musical features will be added, so that musicpy can do more with music.

Thank you for your support~

If you are interested in the latest progress and develop thoughts of musicpy, you could take a look at this repository musicpy_dev

Contact

Discord: Rainbow Dreamer#7122

qq: 2180502841

Bilibili account: Rainbow_Dreamer

email: 2180502841@qq.com / q1036889495@gmail.com

Discussion group:

QQ discussion group: 364834221

Donation

This project is developed by Rainbow Dreamer on his spare time to create an interesting music composition library and a high-level MIDI toolkit. If you feel this project is useful to you and want to support it and it's future development, please consider sponsor this project by clicking the sponsor button, it would help me out a lot.

Reasons Why I Develop This Language and Keep Working on This Project

There are two main reasons why I develop this language. Firstly, compared with project files and MIDI files that simply store unitary information such as notes, intensity, tempo, etc., it would be more meaningful to represent how a piece of music is realized from a compositional point of view, in terms of music theory. Most music is extremely regular in music theory, as long as it is not modernist atonal music, and these rules can be greatly simplified by abstracting them into logical statements of music theory. (A MIDI file with 1000 notes, for example, can actually be reduced to a few lines of code from a music theory perspective.) Secondly, the language was developed so that the composing AI could compose with a real understanding of music theory (instead of deep learning and feeding a lot of data), and the