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I +have already [written an +article](https://blog.platypush.tech/article/Build-your-open-source-multi-room-and-multi-provider-sound-server-with-Platypush-Mopidy-and-Snapcast) +on how to leverage mopidy (with its tons of integrations, including Spotify, +Tidal, YouTube, Bandcamp, Plex, TuneIn, SoundCloud etc.), Snapcast (with its +multi-room listening experience out of the box) and Platypush (with its +automation hooks that allow you to easily create if-this-then-that rules for +your music events) to take your listening experience to the next level, while +using open protocols and easily extensible open-source software. + +There is a feature that I haven't yet covered in my previous articles, and +that's the automation of your music collection. + +Spotify, Tidal and other music streaming services offer you features such as a +_Discovery Weekly_ or _Release Radar_ playlists, respectively filled with +tracks that you may like, or newly released tracks that you may be interested +in. + +The problem is that these services come with heavy trade-offs: + +1. Their algorithms are closed. You don't know how Spotify figures out which + songs should be picked in your smart playlists. In the past months, Spotify + would often suggest me tracks from the same artists that I had already + listened to or skipped in the past, and there's no easy way to tell the + algorithm "hey, actually I'd like you to suggest me more this kind of music - + or maybe calculate suggestions only based on the music I've listened to in + this time range". + +2. Those features are tightly coupled with the service you use. If you cancel + your Spotify subscription, you lose those smart features as well. + Companies like Spotify use such features as a lock-in mechanism - + "you can check out any time you like, but if you do then nobody else will + provide you with our clever suggestions". + +After migrating from Spotify to Tidal in the past couple of months (TL;DR: +Spotify f*cked up their developer experience multiple times over the past +decade, and their killing of libspotify without providing any alternatives was +the last nail in the coffin for me) I felt like missing their smart mixes, +discovery and new releases playlists - and, on the other hand, Tidal took a +while to learn my listening habits, and even when it did it often generated +smart playlists that were an inch below Spotify's. I asked myself why on earth +my music discovery experience should be so tightly coupled to one single cloud +service. And I decided that the time had come for me to automatically generate +my service-agnostic music suggestions: it's not rocket science anymore, there's +plenty of services that you can piggyback on to get artist or tracks similar to +some music given as input, and there's just no excuses to feel locked in by +Spotify, Google, Tidal or some other cloud music provider. + +In this article we'll cover how to: + +1. Use Platypush to automatically keep track of the music you listen to from + any of your devices; +2. Calculate the suggested tracks that may be similar to the music you've + recently listen to by using the Last.FM API; +3. Generate a _Discover Weekly_ playlist similar to Spotify's without relying + on Spotify; +4. Get the newly released albums and single by subscribing to an RSS feed; +5. Generate a weekly playlist with the new releases by filtering those from + artists that you've listened to at least once. + +## Ingredients + +We will use Platypush to handle the following features: + +1. Store our listening history to a local database, or synchronize it with a + scrobbling service like [last.fm](https://last.fm). +2. Periodically inspect our newly listened tracks, and use the last.fm API to + retrieve similar tracks. +3. Generate a discover weekly playlist based on a simple score that ranks + suggestions by match score against the tracks listened on a certain period + of time, and increases the weight of suggestions that occur multiple times. +4. Monitor new releases from the newalbumreleases.net RSS feed, and create a + weekly _Release Radar_ playlist containing the items from artists that we + have listened to at least once. + +This tutorial will require: + +1. A database to store your listening history and suggestions. The database + initialization script has been tested against Postgres, but it should be + easy to adapt it to MySQL or SQLite with some minimal modifications. +2. A machine (it can be a RaspberryPi, a home server, a VPS, an unused tablet + etc.) to run the Platypush automation. +3. A Spotify or Tidal account. The reported examples will generate the + playlists on a Tidal account by using the `music.tidal` Platypush plugin, + but it should be straightforward to adapt them to Spotify by using the + `music.spotify` plugin, or even to YouTube by using the YouTube API, or even + to local M3U playlists. + +## Setting up the software + +Start by installing Platypush with the +[Tidal](https://docs.platypush.tech/platypush/plugins/music.tidal.html), +[RSS](https://docs.platypush.tech/platypush/plugins/rss.html) and +[Last.fm](https://docs.platypush.tech/platypush/plugins/lastfm.html) +integrations: + +``` +[sudo] pip install 'platypush[tidal,rss,lastfm]' +``` + +If you want to use Spotify instead of Tidal then just remove `tidal` from the +list of extra dependencies - no extra dependencies are required for the +[Spotify +plugin](https://docs.platypush.tech/platypush/plugins/music.spotify.html). + +If you are planning to listen to music through mpd/mopidy, then you may also +want to include `mpd` in the list of extra dependencies, so Platypush can +directly monitor your listening activity over the MPD protocol. + +Let's then configure a simple configuration under `~/.config/platypush/config.yaml`: + +```yaml +music.tidal: + # No configuration required + +# Or, if you use Spotify, create an app at https://developer.spotify.com and +# add its credentials here +# music.spotify: +# client_id: client_id +# client_secret: client_secret + +lastfm: + api_key: your_api_key + api_secret: your_api_secret + username: your_user + password: your_password + +# Subscribe to updates from newalbumreleases.net +rss: + subscriptions: + - https://newalbumreleases.net/category/cat/feed/ + +# Optional, used to send notifications about generation issues to your +# mobile/browser. You can also use Pushbullet, an email plugin or a chatbot if +# you prefer. +ntfy: + # No configuration required if you want to use the default server at + # https://ntfy.sh + +# Include the mpd plugin and backend if you are listening to music over +# mpd/mopidy +music.mpd: + host: localhost + port: 6600 + +backend.music.mopidy: + host: localhost + port: 6600 +``` + +Start Platypush by running the `platypush` command. The first time it should +prompt you with a tidal.com link required to authenticate your user. Open it in +your browser and authorize the app - the next runs should no longer ask you to +authenticate. + +Once the Platypush dependencies are in place, let's move to configure the +database. + +## Database configuration + +I'll assume that you have a Postgres database running somewhere, but the script +below can be easily adapted also to other DBMS's. + +Database initialization script (download/pastebin link is +[here](https://paste.fabiomanganiello.com/blacklight/music.sql)): + +```sql +-- New listened tracks will be pushed to the tmp_music table, and normalized by +-- a trigger. +drop table if exists tmp_music cascade; +create table tmp_music( + id serial not null, + artist varchar(255) not null, + title varchar(255) not null, + album varchar(255), + created_at timestamp with time zone default CURRENT_TIMESTAMP, + primary key(id) +); + +-- This table will store the tracks' info +drop table if exists music_track cascade; +create table music_track( + id serial not null, + artist varchar(255) not null, + title varchar(255) not null, + album varchar(255), + created_at timestamp with time zone default CURRENT_TIMESTAMP, + primary key(id), + unique(artist, title) +); + +-- Create an index on (artist, title), and ensure that the (artist, title) pair +-- is unique +create unique index track_artist_title_idx on music_track(lower(artist), lower(title)); +create index track_artist_idx on music_track(lower(artist)); + +-- music_activity holds the listen history +drop table if exists music_activity cascade; +create table music_activity( + id serial not null, + track_id int not null, + created_at timestamp with time zone default CURRENT_TIMESTAMP, + primary key(id) +); + +-- music_similar keeps track of the similar tracks +drop table if exists music_similar cascade; +create table music_similar( + source_track_id int not null, + target_track_id int not null, + match_score float not null, + primary key(source_track_id, target_track_id), + foreign key(source_track_id) references music_track(id), + foreign key(target_track_id) references music_track(id) +); + +-- music_discovery_playlist keeps track of the generated discovery playlists +drop table if exists music_discovery_playlist cascade; +create table music_discovery_playlist( + id serial not null, + name varchar(255), + created_at timestamp with time zone default CURRENT_TIMESTAMP, + primary key(id) +); + +-- This table contains the track included in each discovery playlist +drop table if exists music_discovery_playlist_track cascade; +create table music_discovery_playlist_track( + id serial not null, + playlist_id int not null, + track_id int not null, + primary key(id), + unique(playlist_id, track_id), + foreign key(playlist_id) references music_discovery_playlist(id), + foreign key(track_id) references music_track(id) +); + +-- This trigger normalizes the tracks inserted into tmp_track +create or replace function sync_music_data() + returns trigger as +$$ +declare + track_id int; +begin + insert into music_track(artist, title, album) + values(new.artist, new.title, new.album) + on conflict(artist, title) do update + set album = coalesce(excluded.album, old.album) + returning id into track_id; + + insert into music_activity(track_id, created_at) + values (track_id, new.created_at); + + delete from tmp_music where id = new.id; + return new; +end; +$$ +language 'plpgsql'; + +drop trigger if exists on_sync_music on tmp_music; +create trigger on_sync_music + after insert on tmp_music + for each row + execute procedure sync_music_data(); + +-- (Optional) accessory view to easily peek the listened tracks +drop view if exists vmusic; +create view vmusic as +select t.id as track_id + , t.artist + , t.title + , t.album + , a.created_at +from music_track t +join music_activity a +on t.id = a.track_id; +``` + +Run the script on your database - if everything went smooth then all the tables +should be successfully created. + +## Synchronizing your music activity + +Now that all the dependencies are in place, it's time to configure the logic to +store your music activity to your database. + +If most of your music activity happens through mpd/mopidy, then storing your +activity to the database is as simple as creating a hook on a +[`NewPlayingTrackEvent`](https://docs.platypush.tech/platypush/events/music.html) +that inserts any newly playing track on `tmp_music`. Paste the following +content to a new Platypush user script (e.g. +`~/.config/platypush/scripts/music/sync.py`): + +```python +# ~/.config/platypush/scripts/music/sync.py + +from logging import getLogger + +from platypush.context import get_plugin +from platypush.event.hook import hook +from platypush.message.event.music import NewPlayingTrackEvent + +logger = getLogger('music_sync') + +# SQLAlchemy connection string that points to your database +music_db_engine = 'postgresql+pg8000://dbuser:dbpass@dbhost/dbname' + + +# Hook that react to NewPlayingTrackEvent events +@hook(NewPlayingTrackEvent) +def on_new_track_playing(event, **_): + track = event.track + + # Skip if the track has no artist/title specified + if not (track.get('artist') and track.get('title')): + return + + logger.info( + 'Inserting track: %s - %s', + track['artist'], track['title'] + ) + + db = get_plugin('db') + db.insert( + engine=music_db_engine, + table='tmp_music', + records=[ + { + 'artist': track['artist'], + 'title': track['title'], + 'album': track.get('album'), + } + for track in tracks + ] + ) +``` + +Alternatively, if you also want to sync music activities that happens through +other clients (such as the Spotify/Tidal app or web view, or over mobile +devices), you may consider leveraging Last.fm. Last.fm (or its open alternative +Libre.fm) are _scrobbling_ websites that are compatible with most of the music +players out there. Both Spotify and Tidal support scrobbling, the [Android +app](https://apkpure.com/last-fm/fm.last.android) can grab any music activity +on your phone and scrobble, and there are even [browser +extensions](https://chrome.google.com/webstore/detail/web-scrobbler/hhinaapppaileiechjoiifaancjggfjm?hl=en) +that allow you to record any music activity from any browser tab. + +So an alternative approach may be to send both your mpd/mopidy music activity, +as well as your in-browser or mobile music activity, to last.fm / libre.fm. The +corresponding hook would be: + +```python +# ~/.config/platypush/scripts/music/sync.py + +from logging import getLogger + +from platypush.context import get_plugin +from platypush.event.hook import hook +from platypush.message.event.music import NewPlayingTrackEvent + +logger = getLogger('music_sync') + + +# Hook that react to NewPlayingTrackEvent events +@hook(NewPlayingTrackEvent) +def on_new_track_playing(event, **_): + track = event.track + + # Skip if the track has no artist/title specified + if not (track.get('artist') and track.get('title')): + return + + lastfm = get_plugin('lastfm') + logger.info( + 'Scrobbling track: %s - %s', + track['artist'], track['title'] + ) + + lastfm.scrobble( + artist=track['artist'], + title=track['title'], + album=track.get('album'), + ) +``` + +If you go for the scrobbling way, then you may want to periodically synchronize +your scrobble history to your local database - for example, through a cron that +runs every 30 seconds: + +```python +# ~/.config/platypush/scripts/music/scrobble2db.py + +import logging + +from datetime import datetime + +from platypush.context import get_plugin, Variable +from platypush.cron import cron + +logger = logging.getLogger('music_sync') +music_db_engine = 'postgresql+pg8000://dbuser:dbpass@dbhost/dbname' + +# Use this stored variable to keep track of the time of the latest +# synchronized scrobble +last_timestamp_var = Variable('LAST_SCROBBLED_TIMESTAMP') + + +# This cron executes every 30 seconds +@cron('* * * * * */30') +def sync_scrobbled_tracks(**_): + db = get_plugin('db') + lastfm = get_plugin('lastfm') + + # Use the last.fm plugin to retrieve all the new tracks scrobbled since + # the last check + last_timestamp = int(last_timestamp_var.get() or 0) + tracks = [ + track for track in lastfm.get_recent_tracks().output + if track.get('timestamp', 0) > last_timestamp + ] + + # Exit if we have no new music activity + if not tracks: + return + + # Insert the new tracks on the database + db.insert( + engine=music_db_engine, + table='tmp_music', + records=[ + { + 'artist': track.get('artist'), + 'title': track.get('title'), + 'album': track.get('album'), + 'created_at': ( + datetime.fromtimestamp(track['timestamp']) + if track.get('timestamp') else None + ), + } + for track in tracks + ] + ) + + # Update the LAST_SCROBBLED_TIMESTAMP variable with the timestamp of the + # most recent played track + last_timestamp_var.set(max( + int(t.get('timestamp', 0)) + for t in tracks + )) + + logger.info('Stored %d new scrobbled track(s)', len(tracks)) +``` + +This cron will basically synchronize your scrobbling history to your local +database, so we can use the local database as the source of truth for the next +steps - no matter where the music was played from. + +To test the logic, simply restart Platypush, play some music from your +favourite player(s), and check that everything gets inserted on the database - +even if we are inserting tracks on the `tmp_music` table, the listening history +should be automatically normalized on the appropriate tables by the triggered +that we created at initialization time. + +## Updating the suggestions + +Now that all the plumbing to get all of your listening history in one data +source is in place, let's move to the logic that recalculates the suggestions +based on your listening history. + +We will again use the last.fm API to get tracks that are similar to those we +listened to recently - I personally find last.fm suggestions often more +relevant than those of Spotify's. + +For sake of simplicity, let's map the database tables to some SQLAlchemy ORM +classes, so the upcoming SQL interactions can be notably simplified. The ORM +model can be stored under e.g. `~/.config/platypush/music/db.py`: + +```python +# ~/.config/platypush/scripts/music/db.py + +from sqlalchemy import create_engine +from sqlalchemy.ext.automap import automap_base +from sqlalchemy.orm import sessionmaker, scoped_session + +music_db_engine = 'postgresql+pg8000://dbuser:dbpass@dbhost/dbname' +engine = create_engine(music_db_engine) + +Base = automap_base() +Base.prepare(engine, reflect=True) +Track = Base.classes.music_track +TrackActivity = Base.classes.music_activity +TrackSimilar = Base.classes.music_similar +DiscoveryPlaylist = Base.classes.music_discovery_playlist +DiscoveryPlaylistTrack = Base.classes.music_discovery_playlist_track + + +def get_db_session(): + session = scoped_session(sessionmaker(expire_on_commit=False)) + session.configure(bind=engine) + return session() +``` + +Then create a new user script under e.g. +`~/.config/platypush/scripts/music/suggestions.py` with the following content: + +```python +# ~/.config/platypush/scripts/music/suggestions.py + +import logging + +from sqlalchemy import tuple_ +from sqlalchemy.dialects.postgresql import insert +from sqlalchemy.sql.expression import bindparam + +from platypush.context import get_plugin, Variable +from platypush.cron import cron + +from scripts.music.db import ( + get_db_session, Track, TrackActivity, TrackSimilar +) + + +logger = logging.getLogger('music_suggestions') + +# This stored variable will keep track of the latest activity ID for which the +# suggestions were calculated +last_activity_id_var = Variable('LAST_PROCESSED_ACTIVITY_ID') + + +# A cronjob that runs every 5 minutes and updates the suggestions +@cron('*/5 * * * *') +def refresh_similar_tracks(**_): + last_activity_id = int(last_activity_id_var.get() or 0) + + # Retrieve all the tracks played since the latest synchronized activity ID + # that don't have any similar tracks being calculated yet + with get_db_session() as session: + recent_tracks_without_similars = \ + _get_recent_tracks_without_similars(last_activity_id) + + try: + if not recent_tracks_without_similars: + raise StopIteration( + 'All the recent tracks have processed suggestions') + + # Get the last activity_id + batch_size = 10 + last_activity_id = ( + recent_tracks_without_similars[:batch_size][-1]['activity_id']) + + logger.info( + 'Processing suggestions for %d/%d tracks', + min(batch_size, len(recent_tracks_without_similars)), + len(recent_tracks_without_similars)) + + # Build the track_id -> [similar_tracks] map + similars_by_track = { + track['track_id']: _get_similar_tracks(track['artist'], track['title']) + for track in recent_tracks_without_similars[:batch_size] + } + + # Map all the similar tracks in an (artist, title) -> info data structure + similar_tracks_by_artist_and_title = \ + _get_similar_tracks_by_artist_and_title(similars_by_track) + + if not similar_tracks_by_artist_and_title: + raise StopIteration('No new suggestions to process') + + # Sync all the new similar tracks to the database + similar_tracks = \ + _sync_missing_similar_tracks(similar_tracks_by_artist_and_title) + + # Link listened tracks to similar tracks + with get_db_session() as session: + stmt = insert(TrackSimilar).values({ + 'source_track_id': bindparam('source_track_id'), + 'target_track_id': bindparam('target_track_id'), + 'match_score': bindparam('match_score'), + }).on_conflict_do_nothing() + + session.execute( + stmt, [ + { + 'source_track_id': track_id, + 'target_track_id': similar_tracks[(similar['artist'], similar['title'])].id, + 'match_score': similar['score'], + } + for track_id, similars in similars_by_track.items() + for similar in (similars or []) + if (similar['artist'], similar['title']) + in similar_tracks + ] + ) + + session.flush() + session.commit() + except StopIteration as e: + logger.info(e) + + last_activity_id_var.set(last_activity_id) + logger.info('Suggestions updated') + + +def _get_similar_tracks(artist, title): + """ + Use the last.fm API to retrieve the tracks similar to a given + artist/title pair + """ + import pylast + lastfm = get_plugin('lastfm') + + try: + return lastfm.get_similar_tracks( + artist=artist, + title=title, + limit=10, + ) + except pylast.PyLastError as e: + logger.warning( + 'Could not find tracks similar to %s - %s: %s', + artist, title, e + ) + + +def _get_recent_tracks_without_similars(last_activity_id): + """ + Get all the tracks played after a certain activity ID that don't have + any suggestions yet. + """ + with get_db_session() as session: + return [ + { + 'track_id': t[0], + 'artist': t[1], + 'title': t[2], + 'activity_id': t[3], + } + for t in session.query( + Track.id.label('track_id'), + Track.artist, + Track.title, + TrackActivity.id.label('activity_id'), + ) + .select_from( + Track.__table__ + .join( + TrackSimilar, + Track.id == TrackSimilar.source_track_id, + isouter=True + ) + .join( + TrackActivity, + Track.id == TrackActivity.track_id + ) + ) + .filter( + TrackSimilar.source_track_id.is_(None), + TrackActivity.id > last_activity_id + ) + .order_by(TrackActivity.id) + .all() + ] + + +def _get_similar_tracks_by_artist_and_title(similars_by_track): + """ + Map similar tracks into an (artist, title) -> track dictionary + """ + similar_tracks_by_artist_and_title = {} + for similar in similars_by_track.values(): + for track in (similar or []): + similar_tracks_by_artist_and_title[ + (track['artist'], track['title']) + ] = track + + return similar_tracks_by_artist_and_title + + +def _sync_missing_similar_tracks(similar_tracks_by_artist_and_title): + """ + Flush newly calculated similar tracks to the database. + """ + logger.info('Syncing missing similar tracks') + with get_db_session() as session: + stmt = insert(Track).values({ + 'artist': bindparam('artist'), + 'title': bindparam('title'), + }).on_conflict_do_nothing() + + session.execute(stmt, list(similar_tracks_by_artist_and_title.values())) + session.flush() + session.commit() + + tracks = session.query(Track).filter( + tuple_(Track.artist, Track.title).in_( + similar_tracks_by_artist_and_title + ) + ).all() + + return { + (track.artist, track.title): track + for track in tracks + } +``` + +Restart Platypush and let it run for a bit. The cron will operate in batches of +10 items each (it can be easily customized), so after a few minutes your +`music_suggestions` table should start getting populated. + +## Generating the discovery playlist + +So far we have achieved the following targets: + +- We have a piece of logic that synchronizes all of our listening history to a + local database. +- We have a way to synchronize last.fm / libre.fm scrobbles to the same + database as well. +- We have a cronjob that periodically scans our listening history and fetches + the suggestions through the last.fm API. + +Now let's put it all together with a cron that runs every week (or daily, or at +whatever interval we like) that does the following: + +- It retrieves our listening history over the specified period. +- It retrieves the suggested tracks associated to our listening history. +- It excludes the tracks that we've already listened to, or that have already + been included in previous discovery playlists. +- It generates a new discovery playlist with those tracks, ranked according to + a simple score: + +$$ +\rho_i = \sum_{j \in L_i} m_{ij} +$$ + +Where \( \rho_i \) is the ranking of the suggested _i_-th suggested track, \( +L_i \) is the set of listened tracks that have the _i_-th track among its +similarities, and \( m_{ij} \) is the match score between _i_ and _j_ as +reported by the last.fm API. + +Let's put all these pieces together in a cron defined in e.g. +`~/.config/platypush/scripts/music/discovery.py`: + +```python +# ~/.config/platypush/scripts/music/discovery.py + +import logging +from datetime import date, timedelta + +from platypush.context import get_plugin +from platypush.cron import cron + +from scripts.music.db import ( + get_db_session, Track, TrackActivity, TrackSimilar, + DiscoveryPlaylist, DiscoveryPlaylistTrack +) + +logger = logging.getLogger('music_discovery') + + +def get_suggested_tracks(days=7, limit=25): + """ + Retrieve the suggested tracks from the database. + + :param days: Look back at the listen history for the past days + (default: 7). + :param limit: Maximum number of track in the discovery playlist + (default: 25). + """ + from sqlalchemy import func + + listened_activity = TrackActivity.__table__.alias('listened_activity') + suggested_activity = TrackActivity.__table__.alias('suggested_activity') + + with get_db_session() as session: + return [ + { + 'track_id': t[0], + 'artist': t[1], + 'title': t[2], + 'score': t[3], + } + for t in session.query( + Track.id, + func.min(Track.artist), + func.min(Track.title), + func.sum(TrackSimilar.match_score).label('score'), + ) + .select_from( + Track.__table__ + .join( + TrackSimilar.__table__, + Track.id == TrackSimilar.target_track_id + ) + .join( + listened_activity, + listened_activity.c.track_id == TrackSimilar.source_track_id, + ) + .join( + suggested_activity, + suggested_activity.c.track_id == TrackSimilar.target_track_id, + isouter=True + ) + .join( + DiscoveryPlaylistTrack, + Track.id == DiscoveryPlaylistTrack.track_id, + isouter=True + ) + ) + .filter( + # The track has not been listened + suggested_activity.c.track_id.is_(None), + # The track has not been suggested already + DiscoveryPlaylistTrack.track_id.is_(None), + # Filter by recent activity + listened_activity.c.created_at >= date.today() - timedelta(days=days) + ) + .group_by(Track.id) + # Sort by aggregate match score + .order_by(func.sum(TrackSimilar.match_score).desc()) + .limit(limit) + .all() + ] + + +def search_remote_tracks(tracks): + """ + Search for Tidal tracks given a list of suggested tracks. + """ + # If you use Spotify instead of Tidal, simply replacing `music.tidal` + # with `music.spotify` here should suffice. + tidal = get_plugin('music.tidal') + found_tracks = [] + + for track in tracks: + query = track['artist'] + ' ' + track['title'] + logger.info('Searching "%s"', query) + results = ( + tidal.search(query, type='track', limit=1).output.get('tracks', []) + ) + + if results: + track['remote_track_id'] = results[0]['id'] + found_tracks.append(track) + else: + logger.warning('Could not find "%s" on TIDAL', query) + + return found_tracks + + +def refresh_discover_weekly(): + # If you use Spotify instead of Tidal, simply replacing `music.tidal` + # with `music.spotify` here should suffice. + tidal = get_plugin('music.tidal') + + # Get the latest suggested tracks + suggestions = search_remote_tracks(get_suggested_tracks()) + if not suggestions: + logger.info('No suggestions available') + return + + # Retrieve the existing discovery playlists + # Our naming convention is that discovery playlist names start with + # "Discover Weekly" - feel free to change it + playlists = tidal.get_playlists().output + discover_playlists = sorted( + [ + pl for pl in playlists + if pl['name'].lower().startswith('discover weekly') + ], + key=lambda pl: pl.get('created_at', 0) + ) + + # Delete all the existing discovery playlists + # (except the latest one). We basically keep two discovery playlists at the + # time in our collection, so you have two weeks to listen to them before they + # get deleted. Feel free to change this logic by modifying the -1 parameter + # with e.g. -2, -3 etc. if you want to store more discovery playlists. + for playlist in discover_playlists[:-1]: + logger.info('Deleting playlist "%s"', playlist['name']) + tidal.delete_playlist(playlist['id']) + + # Create a new discovery playlist + playlist_name = f'Discover Weekly [{date.today().isoformat()}]' + pl = tidal.create_playlist(playlist_name).output + playlist_id = pl['id'] + + tidal.add_to_playlist( + playlist_id, + [t['remote_track_id'] for t in suggestions], + ) + + # Add the playlist to the database + with get_db_session() as session: + pl = DiscoveryPlaylist(name=playlist_name) + session.add(pl) + session.flush() + session.commit() + + # Add the playlist entries to the database + with get_db_session() as session: + for track in suggestions: + session.add( + DiscoveryPlaylistTrack( + playlist_id=pl.id, + track_id=track['track_id'], + ) + ) + + session.commit() + + logger.info('Discover Weekly playlist updated') + + +@cron('0 6 * * 1') +def refresh_discover_weekly_cron(**_): + """ + This cronjob runs every Monday at 6 AM. + """ + try: + refresh_discover_weekly() + except Exception as e: + logger.exception(e) + + # (Optional) If anything went wrong with the playlist generation, send + # a notification over ntfy + ntfy = get_plugin('ntfy') + ntfy.send_message( + topic='mirrored-notifications-topic', + title='Discover Weekly playlist generation failed', + message=str(e), + priority=4, + ) +``` + +You can test the cronjob without having to wait for the next Monday through +your Python interpreter: + +```python +>>> import os +>>> +>>> # Move to the Platypush config directory +>>> path = os.path.join(os.path.expanduser('~'), '.config', 'platypush') +>>> os.chdir(path) +>>> +>>> # Import and run the cron function +>>> from scripts.music.discovery import refresh_discover_weekly_cron +>>> refresh_discover_weekly_cron() +``` + +If everything went well, you should soon see a new playlist in your collection +named _Discover Weekly [date]_. Congratulations!