Introduction

This project aims to create an open source music recommendation toolkit with an API-first philiosophy. API-first means that user do no need to download a lot of data before they can start working with Troi -- all the needed data should ideally live in online APIs, making it very easy for someone to get started hacking on music recommendations.

To accomplish this goal, we, the MetaBrainz Foundation, have created and hosted a number of data-sets that can be accessed as a part of this project. For instance, the more stable APIs are hosted on our Labs API page.

The ListenBrainz project offers a number of data sets:

1. Collaborative filtered recordings that suggest what recordings a user should listen to based on their previous listening habits.
2. User statistics that were derived from users recent listening habits.

We will continue to build and host more datasets as time passes. If an API endpoint becomes useful to a greater number of people we will elevate these API endpoints to officially supported endpoints that we ensure are up to date on online at all times.

The project is named after Deanna Troi.

Documentation

Full documentation for Troi is available at troi.readthedocs.org.

Installation for end users

So far we've not uploaded Troi bundles to PyPi -- please use the installation instructions for developers below.

Installation for Development

Linux and Mac

virtualenv -p python3 .ve
source .ve/bin/activate
pip3 install .[tests]
troi --help

Windows

virtualenv -p python .ve
.ve\Scripts\activate.bat
pip install .[tests]
troi --help

Basic commands

List available patches:

troi list

Generate a playlist using a patch:

troi playlist --print [patch-name]

If the patch requires arguments, running it with no arguments will print a usage statement, e.g.

$ troi playlist --print area-random-recordings
Usage: area-random-recordings [OPTIONS] AREA START_YEAR END_YEAR

  Generate a list of random recordings from a given area.

  AREA is a MusicBrainz area from which to choose tracks.
  START_YEAR is the start year.
  END_YEAR is the end year.

Options:
  --help  Show this message and exit.

Running tests

troi test
troi test -v
troi test -v <file to test>

Building Documentation

To build the documentation locally:

pip install .[docs]
cd docs
make clean html

References for the future path of Troi

Troi is a rather primitive tool at this point in time, but as the MetaBrainz projects gather more data, we can improve how we generate playlists. A good overview of the technology and psychology behind playlists and recommendations, see:

• https://www.slideshare.net/BenFields/finding-a-path-through-the-juke-box-the-playlist-tutorial?utm_source=pocket_mylist