Development/Summer of Code/2017

Are you interested in working with MetaBrainz in Google Summer of Code 2017? You're in the right place!

Where to start

New to MetaBrainz?

List of MetaBrainz projects

New to MetaBrainz development and/or GSoC?

Getting started with GSoC

New to the idea of linked open data?

Linked open data article on wikipedia

Ready to apply?

GSoC applications @ community.metabrainz.org

Be aware of the content of our Development/Summer of Code/Application Template

Mentors

Mentor list

Name	IRC nick	Project
Robert Kaye	ruaok	AcousticBrainz, ListenBrainz, MusicBrainz
Michael Wiencek	bitmap	MusicBrainz
Alastair Porter	alastairp	AcousticBrainz, ListenBrainz
Ben Ockmore	LordSputnik	BookBrainz
Sean Burke	Leftmost	BookBrainz
Roman Tsukanov	Gentlecat	CritiqueBrainz, AcousticBrainz, ListenBrainz

Some potential mentors are listed by each project; this is far from a normative list, but it might give you somebody to ask about the project.

Note: Contacting the mentors privately (e.g., via e-mail or private IRC messages) will get you off to a very, very bad start in your relations with us and any application you send us is now almost definitely going to not get accepted.

About proposals

Before you dive in and send a proposal to us through Google, it's a good idea to take some time and learn about the MusicBrainz community. At MusicBrainz we pride ourselves for having a strong community - most of us know each other in some way, and some of us know each other face to face from development summits.

A good way to get a feel of this would be to talk about your ideas and proposals on IRC. However, starting off by sending private messages to potential mentors is not a good way to introduce yourself to the community. Please don't do that!

If you're not sure where to start, Development/Summer of Code/Getting started might help.

Projects

AcousticBrainz

	AcousticBrainz is our new project that crowdsources acoustic information for all music in the world and to make it available to the public. We already have low-level information about more than three million tracks. What we need is a good way for users and developers to interact with all this data and help improve algorithms that are used to analyze it. It would suit someone with experience or an interest in machine learning algorithms, though the majority of the project will probably involve creating infrastructure around our existing algorithms.
	Languages/skills: Python, PostgreSQL, Flask
	Ideas page | Main page | Forums | Blog

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BookBrainz

	BookBrainz is a database of book metadata. This year we're interested in projects that help us get more data. The three suggested ideas to build proposals around are data importing, a web API and gamification of editing. Please see our sub-project ideas page for information on getting started and more details about the ideas themselves.
	Top 3 Desired Skills: Node.js, Python, SQL
	Ideas page | Main page | Forums

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CritiqueBrainz

	Fills the gap between music critics and raw data by providing a platform created for the sole purpose of Creative Commons licensed reviews.
	Languages/skills: Python, Flask, SQL, PostgreSQL
	Ideas page | Main page | Forums

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ListenBrainz

	An open source music website that allows users to import their listen history. One of the goals is for this data to be used for building open music recommendation systems.
	Languages/skills: Python
	Ideas page | Main page

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MusicBrainz

	A community-maintained open source music encyclopedia that collects music metadata and makes it available to the public.
	Languages/skills: JavaScript (React), Perl, Python, PostgreSQL, SQL
	Ideas page | Main page | Forums

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MusicBrainz Picard

Someone fill in
	Languages/skills: Python, QT
	Ideas page | [page] | Forums

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MusicBrainz Picard

Qt5/Py3 Port

Proposed Mentors: zas/bitmap
Languages/skills: Python, PyQt5

Picard is going to be receiving a complete make-over code/feature/UI wise for v2.0. A part of the v2.0 plans is porting the existing code to PyQt5/Py3 from PyQt4/py2 to allow for future support and better encoding compatibility along with new features of Qt5(such as High DPI scaling, better Widget and networking support and better cross-platform compatibility) and along with all the bug fixes that come with PyQt5 which will help cleaning up the code-base for Picard.

For more information see: PICARD-588 PICARD-960

Picard Plugins API v2

Proposed Mentors: zas/bitmap
Languages/skills: Python, PyQt5, Flask

Picard 2.0 is going to be PyQt5 based, which means all the existing plugins have to be ported to PyQt5/Py3. Since Picard v1 plugins will be incompatible with v2 and vice versa, we need to implement a new v2 end-point for the Picard website. There is also a need of providing a uniform GUI api for plugins to allow quick GUI option settings, i18n support and UI uniformity with the rest of the Picard code. Also, additional metadata headers need to be implemented to allow cross-platform compatibility checks.

For more info see: PICARD-977