一个推荐引擎游乐场，有望使播放音乐推荐变得容易。_Python_下载.zip

# 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](https://labs.api.listenbrainz.org). 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](https://en.wikipedia.org/wiki/Deanna_Troi). # Documentation Full documentation for Troi is available at [troi.readthedocs.org](https://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 -r requirements.txt -r requirements_test.txt python3 -m troi.cli --help ``` **Windows** ``` virtualenv -p python .ve .ve\Scripts\activate.bat pip install -r requirements.txt -r requirements_test.txt python -m troi.cli --help ``` ## Basic commands List available patches: python -m troi.cli list Generate a playlist using a patch: python -m troi.cli playlist --print [patch-name] If the patch requires arguments, running it with no arguments will print a usage statement, e.g. $ python -m troi.cli 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 ``` python3 -m troi.cli test python3 -m troi.cli test -v python3 -m troi.cli test -v <file to test> ``` ## Building Documentation To build the documentation locally: cd docs pip install -r requirements.txt 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