borscht-hs

Borscht is in development! Many of the features below have been implemented in some form, but have not yet been glued together into a cohesive experience. Borscht is my way of practicing Haskell, so it's a Frankenstein's monster of different packages and coding styles.

borscht is a command line tool for organizing your personal music library.

• Search for missing music metadata from the Discogs and MusicBrainz databases.
• (in progress) Write custom Datalog inference rules to automatically tag and re-tag your music, and create playlists from saved Datalog queries.

borscht takes inspiration from beets, with a few key differences:

• borscht works natively with both MusicBrainz and Discogs, whereas the Discogs plugin for beets is has been somewhat neglected
• beets assumes your music is organized into albums, while borscht is happy to work with individual songs
• borscht has a powerful tagging system based on datalog
• borscht helps you assign an acceptable set of metadata to digital music files, but is not too concerned with preserving the correspondence between your digial and physical libraries
• borscht is optimized for my personal use case, and doesn't have all the same bells and whistles as beets

About

I created borscht not only to create a music database that suits my use case, but also to practice writing non-trivial applications with Haskell. Before this project, my experience was mostly small single-file experiments compiled directly with ghc. Since the goal of this project was to learn as much as possible about "getting stuff done" in Haskell, the code is a bit of a mishmash of different styles, abstractions, and language extensions. During this project, I gained experience with the following topics:

• I learned how to use cabal to manage project dependencies
• I use req to make HTTP requests, including API authentication
• I use aeson to parse JSON responses from the Discogs and MusicBrainz APIs
• (in progress) I use persistent to manage a sqlite database for music libraries created with borscht
• I use mtl to manage a monad transformer stack
• I wrote a monadic parser combinator for Datalog inference rules R(X,Y) :- P(X,Z), P(Z,Y).
• (in progress) I implemented semi-naive evaluation with stratified negation for Datalog, which powers the music tagging system.
• I wrote a foreign function interface wrapper for the Kakasi C library, which transliterates Japanese kanji to romaji.
• I merged a pull request into the Byline package adding support for vivid ANSI terminal colors, and a second one to repair an unlawful semigroup instance.

Here's a list of some tangential topics that I read about while working on borscht. These are all really interesting to me and I hope to work with them directly on future projects.

• I learned about stm concurrency in Haskell by reading Peyton-Jones 2007, "Beautiful Concurrency", and inspecting the source code for the rate-limit package, which borscht uses to respect the rate limit intervals for API requests to the Discogs and MusicBrainz databases
• While reading about Datalog, I learned about the datafun, flix projects, which extend Datalog with cool features like incrementalization, function abstraction, and lattices. I hope to add some of these features to my own datalog implementation! There's also the incremental differential-dataflow project.

FAQ

Why the name? Borscht is a type of soup made from beets!

What music do you listen to? Check out Tinariwen, Dakh Daughters, and Shaolin Afronauts.

Development

Dependency: text-icu

sudo apt install libicu-dev

Dependency: taglib

Borscht uses htaglib, which requires that we install TagLib separately. There's not much documentation, but the following worked for me on Ubuntu 20.04.

sudo apt install libtagc0-dev

Dependency: kakasi

The ICU library cannot transliterate Japanese kanji characters. Instead, Borscht relies on kakasi, which is not commonly avilable in package managers. First, download the kakasi source, then

$ ./config
$ make
$ make install

After installing, the necessary header and static library files should be found in /usr/local. For a local install, use ./config --prefix=$(pwd)/build before running make.

./usr/local/include/libkakasi.h
./usr/local/lib/libkakasi.a

Cabal statically links the kakasi library from these locations.