Smarter Playlists

Smarter Playlists let's you get the playlists you want by exporting you iTunes data, collecting it to give more in-depth play data over time.

Import iTunes music data to PostgreSQL, build an actual play history, make playlists with SQL and export them back out to iTunes.

This repo consists of two separate Python scripts. One to move data from iTunes to Postgres and the other to go back the other way.

Import to Postgres

To import your music data to a local postgres database you just need to follow a few simple steps and then run the import-to-postgres.py script.

Prerequisites

• Python 3.7+
• python3-psycopg2
• Postgres running locally
• iTunes configured to "Share Library XML with other Applications" in Preferences > Advanced
• Basic SQL knowledge to create a playlist of your liking.

python3 ./import-to-postgres.py --library "/Users/Stephan5/Music/iTunes/iTunes Music Library.xml" --db "music" --port 5432 --schema "public" --user "postgres" --pass "postgres"

Once the script has successfully run, you should have artist, album, track and play tables in your choosen schema.

The script can be re-run as many time as desired and simply updates the existing tables with any new tracks/play information.

The play table uses the "last played" data from itunes to create a history of plays - albeit inaccurate initially. The idea is that over time, running the script frequently will produce an accurate play history, allowing you to create Smarter Playlists.

Export to Playlist

Create a View

To later export a view or table from your postgres music database you simply run the other script, named export-to-playlist.py. This can produce an M3U playlist file that can be automatically imported to iTunes.

For example, you might create a view such as the following to create a playlist for a month of the year

CREATE OR REPLACE VIEW jan_2019 AS
 SELECT playlist_tracks.itunes_id,
        ROW_NUMBER() OVER (ORDER BY playlist_tracks.count DESC) AS row_number,
        playlist_tracks.count,
        playlist_tracks.track_name
   FROM (SELECT play.track_id,
                track.itunes_id,
                track.track_name,
                COUNT(*) AS count,
                ROW_NUMBER() OVER (PARTITION BY track.album_id ORDER BY (COUNT(*)) DESC) AS album_rows,
                ROW_NUMBER() OVER (PARTITION BY track.artist_id ORDER BY (COUNT(*)) DESC) AS artist_rows
           FROM play
           JOIN track USING (track_id)
           JOIN artist USING (artist_id)
           JOIN album USING (album_id, artist_id)
          WHERE DATE_PART('month'::text, play.played_at) = '1':: DOUBLE PRECISION
            AND DATE_PART('year'::text, play.played_at) = '2019':: DOUBLE PRECISION
          GROUP BY play.track_id, track.track_name, track.itunes_id, track.album_id, track.artist_id) AS playlist_tracks
  WHERE playlist_tracks.album_rows <= 2 
    AND playlist_tracks.artist_rows <= 5 
    AND playlist_tracks.count > 1
  GROUP BY playlist_tracks.track_id, playlist_tracks.track_name, playlist_tracks.itunes_id, playlist_tracks.count
  ORDER BY playlist_tracks.count DESC
  LIMIT 50;

M3U Format

To export a pre-made SQL view like the one above as an M3U playlist you can run the export script without the format argument (M3U is now the default)

python3 ./export-to-playlist.py -name "January 2019" -view "jan_2019" --library "/Users/Stephan5/Music/iTunes/iTunes Music Library.xml" --db "music" --port 5432 --schema "public" --user "postgres" --pass "postgres"

You can also use the bash script update_playlist.sh to auto import it into iTunes for you.

/bin/sh /Users/Stephan5/Development/smarter-playlists/update_playlist.sh "January 2019" jan_2019
 

XML Format

To export a view to an XML playlist, the export script needs be run with the --format argument.

python3 ./export-to-playlist.py --format XML -name "January 2019" -view "jan_2019" --library "/Users/Stephan5/Music/iTunes/iTunes Music Library.xml" --db "music" --port 5432 --schema "public" --user "postgres" --pass "postgres"

This would output an XML file labeled January 2019.xml which can be imported into iTunes using File > Library > Import Playlist...

Automation

A simple way to automate the continual importing of itunes data into the Postgres DB and timely export of updated playlists, cron can be used like so...

5  */2 * * * /usr/local/bin/python3 /Users/stephan/Development/smarter-playlists/import-to-postgres.py >/dev/null 2>&1
10 */2 * * * /bin/sh /Users/Stephan5/Development/smarter-playlists/update_playlist.sh "Top 500" top_500
11 */2 * * * /bin/sh /Users/Stephan5/Development/smarter-playlists/update_playlist.sh "Middle 500" middle_500
12 */2 * * * /bin/sh /Users/Stephan5/Development/smarter-playlists/update_playlist.sh "Top 2019" year_2019
13 */2 * * * /bin/sh /Users/Stephan5/Development/smarter-playlists/update_playlist.sh "January 2019" jan_2019
14 */2 * * * /bin/sh /Users/Stephan5/Development/smarter-playlists/update_playlist.sh "Feburary 2019" feb_2019
15 */2 * * * /bin/sh /Users/Stephan5/Development/smarter-playlists/update_playlist.sh "March 2019" mar_2019
16 */2 * * * /bin/sh /Users/Stephan5/Development/smarter-playlists/update_playlist.sh "April 2019" april_2019

iTunes must be kept open at all times for this to work effectively.

Acknowledgements

These scripts borrow heavily from itunes-to-sql and swinsian2itlxml for inspiration.