This program will first get the metadata of various songs from metadata providers like musicbrainz, and then search for download links on pages like bandcamp. Then it will download the song and edit the metadata accordingly.
Go to file
2022-11-24 14:34:36 +01:00
.idea Documentation fixes 2022-11-22 03:24:48 -05:00
.VSCodeCounter new commit 2022-11-23 11:33:24 +01:00
assets added source table to the database 2022-11-16 13:43:52 +01:00
src refactored imports, so every important function can be imported directly from the 'root module' music_kraken 2022-11-24 14:34:36 +01:00
.gitignore Some cli improvements 2022-11-22 03:24:25 -05:00
build.sh new build and upload 2022-11-24 12:37:44 +01:00
database_structure.sql added cli in appropriate file 2022-11-23 08:10:22 +01:00
LICENSE Initial commit 2022-10-14 13:02:01 +02:00
notes.md documented new module structure and fixed up readme 2022-11-16 10:30:00 +01:00
pyproject.toml new build and upload 2022-11-24 12:37:44 +01:00
README.md readme 2022-11-24 12:10:00 +01:00
requirements.txt dsf 2022-11-11 00:21:30 +01:00
setup.py should be ready for a new build :) 2022-11-23 09:20:28 +01:00

Music Kraken

Installation

You can find and get this project from either PyPI as Python-Package or simply the source code from GitHub. Note that even though everything SHOULD work cross Plattform, I only tested it on Ubuntu. If you enjoy this project, feel free to give it a Star on GitHub.

# install it with
pip install music-kraken

# and simply run it like this:
music-kraken

Notes for WSL

If you choose to run it in WSL, make sure ~/.local/bin is added to your $PATH #2

Quick-Guide

Genre: First the cli asks you to input a gere you want to download to. The options it gives you (if it gives you any) are all the folders you got in the music directory. You also can just input a new one.

What to download: After that it prompts you for a search. Here are a couple examples how you can search:

> #a <any artist>
searches for the artist <any artist>

> #a <any artist> #r <any releas>
searches for the release (album) <any release> by the artist <any artist>

> #r <any release> Me #t <any track>
searches for the track <any track> from the release <any relaese>

After searching with this syntax it prompts you with multiple results. You can either choose one of those by inputing its id int or you can search for a new query.

After you chose either an artist, a release group, a release or a track by its id, download it by inputing the string ok. My downloader will download it automatically for you.


Programming Interface / use as Library

If you want to use this project, or parts from it in your own projects from it, make sure to be familiar with Python Modules. Further and better documentation including code examples are yet to come, so here is the rough module structure for now. (should be up-to-date but no guarantee)

Music Kraken can be imported like this:

import music_kraken as mk

if you simply want to run the builtin minimal cli just do this:

mk.cli()

Search for Metadata

The whole programm takes the data it processes further from the cache, a sqlite database. So before you can do anything, you will need to fill it with the songs you want to download.
For now the base of everything is musicbrainz, so you need to get the musicbrainz id and the type the id corresponds to (artist/release group/release/track). To get this you first have to initialize a search object (music_kraken.metadata.metadata_search.Search).

search_object = mk.metadata.metadata_search.Search()

Then you need an initial "text search" to get some options you can choose from. For this you can either specify artists releases and whatever directly with one of the following functions:

# you can directly specify artist, release group, release or recording/track
multiple_options = search_object.search_from_text(artist=input("input the name of the artist: "))
# you can specify a query see the simple integrated cli on how to use the query
multiple_options = search_object.search_from_query(query=input("input the query: "))

both possible methods return an instance of MultipleOptions, which can be directly converted to a string.

print(multiple_options)

After the first "text search" you can either again search the same way as before, or you can further explore one of the options from the previous search.
To explore and select one options from MultipleOptions, simply call Search.choose(self, index: int). The index represents the number in the previously returned instance of MultipleOptions. The selected Option will be selected and can be downloaded in the next step.

Thus, this has to be done after either search_from_text or search_from_query

# choosing the best matching band
multiple_options = search_object.choose(0)
# choosing the first ever release group of this band
multiple_options = search_object.choose(1)
# printing out the current options
print(multiple_options)

This process can be repeated indefinitely (until you run out of memory). A search history is kept in the Search instance. You could go back to the previous search (without any loading time) like this:

multiple_options = search.get_previous_options()

Downloading Metadata / Filling up the Cache

If you selected the Option you want with Search.choose(i), you can finally download the metadata of either:

  • an artist (the whole discography)
  • a release group
  • a release
  • a track/recording To download you need the selected Option Object (music_kraken.metadata.metadata_search.Option) it is simply stored in Search.current_option.

If you already know what you want to download you can skip all the steps above and just create a dictionary like this and use it later (might change and break after I add multiple metadata sources which I will):

download_dict = {
    'type': option_type,
    'id': musicbrainz_id
}

The option type is a string (I'm sorry for not making it an enum I know its a bad pratice), which can have following values:

  • 'artist'
  • 'release_group'
  • 'release'
  • 'recording'

PAY ATTENTION TO TYPOS, ITS CASE SENSITIVE

The musicbrainz id is just the id of the object from musicbrainz.

# in this example I will choose the previous selected option.
option_to_download = search_object.current_option
print(option_to_download)

download_dict = {
    'type': option_to_download.type,
    'id': option_to_download.id
}

If you got the Option instance you want to download and created the dictionary, then downloading the metadata is really straight forward, so I just show the code.

# I am aware of abstrackt classes
metadata_downloader = mk.metadata.metadata_fetch.MetadataDownloader()
metadata_downloader.download(download_dict)

After following those steps, it might take a couple seconds/minutes to execute, but then the Cache will be filled.

Cache / Temporary Database

All the data, the functions that download stuff use, can be gotten from the temporary database / cache. You can get the database object like this:

cache = mk.database.temp_database.temp_database
print(cache)

When fetching any song data from the cache, you will get it as Song object (music_kraken.database.song.Song). There are multiple methods to get different sets of Songs. The names explain the methods pretty well:

# gets a single track specified by the id
cache.get_track_metadata(id: str)

# gets a list of tracks.
cache.get_tracks_to_download()
cache.get_tracks_without_src()
cache.get_tracks_without_isrc()
cache.get_tracks_without_filepath()

the id always is a musicbrainz id and distinct for every track.

Setting the Target

By default the music downloader doesn't know where to save the music file, if downloaded. To set those variables (the directory to save the file in and the filepath), it is enough to run one single command:

# adds file path, file directory and the genre to the database 
mk.target.set_target.UrlPath(genre="some test genre")

The concept of genres is too loose, to definitly say, this band exclusively plays this genre, or this song is this genre. This doesn't work manually, this will never work automatically. Thus I've decided to just use the genre as category, to sort the artists and songs by. Most Music players support that.

As a result of this decision you will have to pass the genre in this function (actually its a class but it doesn't make any difference).

This is most likely the most usefull and unique feature of this Project. If the cache is filled you can get audio sources for the songs you only have the metadata. This works for most songs. I'd guess for about 97% (?)

# this is how you do it.
mk.audio_source.fetch_source.Download()

Now the audio sources are int the cache, and you can get them as mentioned above (Song.sources: List[Source]).

Downloading the Audio

If the target paths fields and audio sources are set in the database field, then the audio files can just be downloaded and automatically tagged like this:

mk.audio_source.fetch_audio.Download()

# after that the lyrics can be added
mk.lyrics.lyrics.fetch_lyrics()

Metadata

First the metadata has to be downloaded. The best api to do so is undeniably Musicbrainz. This is a result of them being a website with a large Database spanning over all Genres.

Musicbrainz

Musicbrainz Data Scheme

To fetch from Musicbrainz we first have to know what to fetch. A good start is to get an input querry, which can be just put into the MB-Api. It then returns a list of possible artists, releases and recordings.

If the following chosen element is an artist, its discography + a couple tracks are printed, if a release is chosen, the artists + tracklist + release is outputted, If a track is chosen its artists and releases are shown.

Up to now it doesn't if the discography or tracklist is chosen.

Metadata to fetch

I orient on which metadata to download on the keys in mutagen.EasyID3 . Following I fetch and thus tag the MP3 with:

  • title
  • artist
  • albumartist
  • tracknumber
  • albumsort can sort albums cronological
  • titlesort is just set to the tracknumber to sort by track order to sort correctly
  • isrc
  • musicbrainz_artistid
  • musicbrainz_albumid
  • musicbrainz_albumartistid
  • musicbrainz_albumstatus
  • language
  • musicbrainz_albumtype
  • releasecountry
  • barcode

albumsort/titlesort

Those Tags are for the musicplayer to not sort for Example the albums of a band alphabetically, but in another way. I set it just to chronological order

isrc

This is the international standart release code. With this a track can be identified 99% of the time, if it is known and the website has a search api for that. Obviously this will get important later.

Download

Now that the metadata is downloaded and cached, download sources need to be sound, because one can't listen to metadata. Granted it would be amazing if that would be possible.

Musify

The quickest source to get download links from is to my knowledge musify. Its a russian music downloading page, where many many songs are available to stream and to download. Due to me not wanting to stress the server to much, I abuse a handy feature nearly every page where you can search suff has. The autocomplete api for the search input. Those always are quite limited in the number of results it returns, but it is optimized to be quick. Thus with the http header Connection set to keep-alive the bottleneck defently is not at the speed of those requests.

For musify the endpoint is following: https://musify.club/search/suggestions?term={title} If the http headers are set correctly, then searching for example for "Lorna Shore" yields following result:

[
    {
        "id":"Lorna Shore",
        "label":"Lorna Shore",
        "value":"Lorna Shore",
        "category":"Исполнители",
        "image":"https://39s.musify.club/img/68/9561484/25159224.jpg",
        "url":"/artist/lorna-shore-59611"       
    },
    {"id":"Immortal","label":"Lorna Shore - Immortal (2020)","value":"Immortal","category":"Релизы","image":"https://39s-a.musify.club/img/70/20335517/52174338.jpg","url":"/release/lorna-shore-immortal-2020-1241300"},
    {"id":"Immortal","label":"Lorna Shore - Immortal","value":"Immortal","category":"Треки","image":"","url":"/track/lorna-shore-immortal-12475071"}
]

This is a shortened example for the response the api gives. The results are very Limited, but it is also very efficient to parse. The steps I take are:

  • call the api with the query being the track name
  • parse the json response to an object
  • look at how different the title and artist are on every element from the category Треки, translated roughly to track or release.
  • If they match get the download links and cache them.

Youtube

Herte the isrc plays a huge role. You probably know it, when you search on youtube for a song, and the music videos has a long intro or the first result is a live version. I don't want those in my music collection, only if the tracks are like this in the official release. Well how can you get around that?

Turns out if you search for the isrc on youtube the results contain the music, like it is on the official release and some japanese meme videos. The tracks I wan't just have the title of the released track, so one can just compare those two.

For searching, as well as for downloading I use the programm youtube-dl, which also has a programming interface for python.

There are two bottlenecks with this approach though:

  1. youtube-dl is just slow. Actually it has to be, to not get blocked by youtube.
  2. Ofthen musicbrainz just doesn't give the isrc for some songs.

Lyrics

To get the Lyrics, I scrape them, and put those in the USLT ID3 Tags of for example mp3 files. Unfortunately some players, like the one I use, Rhythmbox don't support USLT Lyrics. So I created an Plugin for Rhythmbox. You can find it here: https://github.com/HeIIow2/rythmbox-id3-lyrics-support.

Genius

For the lyrics source the page https://genius.com/ is easily sufficient. It has most songs. Some songs are not present though, but that is fine, because the lyrics are optional anyways.