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spotifyr is a wrapper for pulling track audio features and other information from Spotify's Web API in bulk. By automatically batching API requests, it allows you to enter an artist's name and retrieve their entire discography in seconds, along with Spotify's audio features and track/album popularity metrics. You can also pull song and playlist information for a given Spotify User (including yourself!).


Development version (recommended)


The development version now imports the geniusR package from Josiah Parry, which you can install with:


(Note that this is separate from the geniusr package currently on CRAN)

CRAN version 1.0.0 (Note: this is somewhat outdated, as it takes extra time to submit and pass CRAN checks)



First, set up a Dev account with Spotify to access their Web API here. This will give you your Client ID and Client Secret. Once you have those, you can pull your access token into R with get_spotify_access_token().

The easiest way to authenticate is to set your credentials to the System Environment variables SPOTIFY_CLIENT_ID and SPOTIFY_CLIENT_SECRET. The default arguments to get_spotify_access_token() (and all other functions in this package) will refer to those. Alternatively, you can set them manually and make sure to explicitly refer to your access token in each subsequent function call.

Sys.setenv(SPOTIFY_CLIENT_ID = 'xxxxxxxxxxxxxxxxxxxxx')
Sys.setenv(SPOTIFY_CLIENT_SECRET = 'xxxxxxxxxxxxxxxxxxxxx')

access_token <- get_spotify_access_token()


What was The Beatles' favorite key?

beatles <- get_artist_audio_features('the beatles')

beatles %>% 
    count(key_mode, sort = TRUE) %>% 
    head(5) %>% 
key_mode n
C major 46
D major 41
G major 38
A major 36
E major 21

Get your most recently played tracks

get_my_recently_played(limit = 5) %>% 
track_name artist_name album_name played_at_utc context_type context_uri context_spotify_url album_type track_number track_popularity explicit album_release_date album_img track_uri artist_uri album_uri track_preview_url track_spotify_url
HoursDaysMonthsSeasons Nathan Fake Providence 2018-06-23 22:18:21 NA NA NA album 3 34 FALSE NA https://i.scdn.co/image/77560c6cccc524891f930353b98a7b5ff7ec38f3 3ahMheJQ0ukl1edNuTRSfr 5rZVjGkZZI4TnpMHQwrxfG 6m2Yw1xMhp90rwUnOdtBcp https://p.scdn.co/mp3-preview/cad8071ea845ea8e08462d0d0075c88ca7598a81?cid=0cfbcde7a276401c891d1ba876c1ebb7 https://open.spotify.com/track/3ahMheJQ0ukl1edNuTRSfr
Deceiver Loscil Monument Builders 2018-06-23 22:13:38 NA NA NA album 5 36 FALSE NA https://i.scdn.co/image/b1fd8f0015767b736324feb28d8c4293b32dfbfd 5ziYoXutr7LlxWtJNDnRG4 3GM5cpCBadq2PMHjFoEvhK 1anZBWOeghB5twG4CyJdoc https://p.scdn.co/mp3-preview/83bbf815785f71e51816d24d21aad9adb3458207?cid=0cfbcde7a276401c891d1ba876c1ebb7 https://open.spotify.com/track/5ziYoXutr7LlxWtJNDnRG4
Txt (MSGS) Mndsgn Yawn Zen 2018-06-23 22:11:11 NA NA NA album 9 33 FALSE NA https://i.scdn.co/image/b5a4c363b2cb30669e334f5b5a34d91ea904a8f6 6keqH1nqtS2j3DOovYwGFU 4GcpBLY8g8NrmimWbssM26 5UNxfgrTnkQeVxFSdkAbCp https://p.scdn.co/mp3-preview/50c8bd2809482f479b55c6029b4e05756d7b4e86?cid=0cfbcde7a276401c891d1ba876c1ebb7 https://open.spotify.com/track/6keqH1nqtS2j3DOovYwGFU
A Grass Day Groundislava Groundislava 2018-06-23 22:10:05 NA NA NA album 3 9 FALSE NA https://i.scdn.co/image/ce3c6e3d79195edbcca8734e3ddcac5f51f22cd5 7CgOsQpzjHToqAfIUmWn4h 2Y2gruKUC2cAjhe0h2RpzV 2tjaNznEZzzGHFZw6UiErj https://p.scdn.co/mp3-preview/c50bf0ab2f50f7740e7c451c20b7a3826234b648?cid=0cfbcde7a276401c891d1ba876c1ebb7 https://open.spotify.com/track/7CgOsQpzjHToqAfIUmWn4h
A Grass Day Groundislava Groundislava 2018-06-23 22:09:27 NA NA NA album 3 9 FALSE NA https://i.scdn.co/image/ce3c6e3d79195edbcca8734e3ddcac5f51f22cd5 7CgOsQpzjHToqAfIUmWn4h 2Y2gruKUC2cAjhe0h2RpzV 2tjaNznEZzzGHFZw6UiErj https://p.scdn.co/mp3-preview/c50bf0ab2f50f7740e7c451c20b7a3826234b648?cid=0cfbcde7a276401c891d1ba876c1ebb7 https://open.spotify.com/track/7CgOsQpzjHToqAfIUmWn4h

Find your all time favorite artists

get_my_top_artists(time_range = 'long_term', limit = 5) %>% 
artist_name artist_uri artist_img artist_genres artist_popularity artist_num_followers artist_spotify_url
Radiohead 4Z8W4fKeB5YxbusRsdQVPb https://i.scdn.co/image/afcd616e1ef2d2786f47b3b4a8a6aeea24a72adc alternative rock, art rock, melancholia, modern rock, permanent wave, rock 79 3218634 https://open.spotify.com/artist/4Z8W4fKeB5YxbusRsdQVPb
Onra 2sAlo7Fey5cqBk5WJILSd8 https://i.scdn.co/image/06280e94f233f6c49f5fdf980dd12d51ba11fa91 alternative hip hop, chillhop, ninja, trip hop, wonky 53 70262 https://open.spotify.com/artist/2sAlo7Fey5cqBk5WJILSd8
Flying Lotus 29XOeO6KIWxGthejQqn793 https://i.scdn.co/image/96a2af0c3ea3654121a2bdc55731e6ef5034be87 alternative hip hop, chillwave, electronic, escape room, glitch, glitch hop, hip hop, indie r&b, indietronica, intelligent dance music, wonky 59 360262 https://open.spotify.com/artist/29XOeO6KIWxGthejQqn793
Teebs 2L2unNFaPbDxjg3NqzpqhJ https://i.scdn.co/image/9554a83f7f84e01a989c6633f5d0e1d174323986 abstract beats, bass music, chillwave, wonky 42 46614 https://open.spotify.com/artist/2L2unNFaPbDxjg3NqzpqhJ
Four Tet 7Eu1txygG6nJttLHbZdQOh https://i.scdn.co/image/f96458025a0640bf1d3c8f764a42ec21d4db1eae alternative dance, chamber psych, electronic, indie r&b, indietronica, intelligent dance music, microhouse, new rave, nu jazz, trip hop 63 246691 https://open.spotify.com/artist/7Eu1txygG6nJttLHbZdQOh

Find your favorite tracks at the moment

get_my_top_tracks(time_range = 'short_term', limit = 5) %>% 
track_name artist_name album_name album_type track_number track_popularity explicit album_release_date album_img track_uri artist_uri album_uri track_preview_url track_spotify_url
Wake and Bake Fleece Scavenger ALBUM 2 39 TRUE 2015-01-20 https://i.scdn.co/image/beab03ac56f835bc228082d9b3709c1dcfb143b2 1ed5ib8UKeZsQaN2GFbmrS 3M8JKaNdIRChzvxVK1XxKm 2RaZ55erDzUKE0zstJ3T0x https://p.scdn.co/mp3-preview/cf6b19d95a0ca8fd33e882f8995c66ad0592a869?cid=null https://open.spotify.com/track/1ed5ib8UKeZsQaN2GFbmrS
Riverside Fleece Voyager ALBUM 5 33 FALSE 2017-01-19 https://i.scdn.co/image/158a2df106b819d5a72227e33d5fbfb51cef21ab 5jBsnG7CPKNNKeR7DmT9FU 3M8JKaNdIRChzvxVK1XxKm 2PuXMzeWFG1N7meAXFVMoq https://p.scdn.co/mp3-preview/1306392012bd8f78fad728c38b3b4ddcf5987b65?cid=null https://open.spotify.com/track/5jBsnG7CPKNNKeR7DmT9FU
Under the Light Fleece Voyager ALBUM 1 38 FALSE 2017-01-19 https://i.scdn.co/image/158a2df106b819d5a72227e33d5fbfb51cef21ab 6HBSSVm0X3z178D6FaXj9d 3M8JKaNdIRChzvxVK1XxKm 2PuXMzeWFG1N7meAXFVMoq https://p.scdn.co/mp3-preview/858208e5482a9932b04c0f8270118fbd6813691a?cid=null https://open.spotify.com/track/6HBSSVm0X3z178D6FaXj9d
Jynweythek Aphex Twin Drukqs ALBUM 1 40 FALSE 2001-10-22 https://i.scdn.co/image/0ecee6d7885e1e7cbe8ff5284706a3f0046d5748 7etelDpVxaPTzmeZrYo8Qy 6kBDZFXuLrZgHnvmPu9NsG 1maoQPAmw44bbkNOxKlwsx https://p.scdn.co/mp3-preview/4ca837c390dc6a05aae2f590bbc2aa6a5d495c10?cid=null https://open.spotify.com/track/7etelDpVxaPTzmeZrYo8Qy
Vibras J Balvin Vibras ALBUM 1 70 FALSE 2018-05-25 https://i.scdn.co/image/cc56f48efc4285caaa8e895337846f5174bf3989 2EEjiKbE4pAjX49TrBzw1X 1vyhD5VmyZ7KMfW5gqLgo5 5kprdYds6oZb4iSldfflOT NA https://open.spotify.com/track/2EEjiKbE4pAjX49TrBzw1X

What's the most joyful Joy Division song?

My favorite audio feature has to be "valence," a measure of musical positivity.

joy <- get_artist_audio_features('joy division')
joy %>% 
    arrange(-valence) %>% 
    select(track_name, valence) %>% 
    head(5) %>% 
track_name valence
These Days 0.949
Passover - 2007 Remastered Version 0.941
Colony - 2007 Remastered Version 0.808
Atrocity Exhibition - 2007 Remastered Version 0.787
Wilderness 0.775
Now if only there was some way to plot joy...

Joyplot of the emotional rollercoasters that are Joy Division's albums

#> Loading required package: ggridges
#> The ggjoy package has been deprecated. Please switch over to the
#> ggridges package, which provides the same functionality. Porting
#> guidelines can be found here:
#> https://github.com/clauswilke/ggjoy/blob/master/README.md

ggplot(joy, aes(x = valence, y = album_name)) + 
    geom_joy() + 
    theme_joy() +
    ggtitle("Joyplot of Joy Division's joy distributions", subtitle = "Based on valence pulled from Spotify's Web API with spotifyr")
#> Picking joint bandwidth of 0.112

Danceability of Thom Yorke


tots <- map_df(c('radiohead', 'thom yorke', 'atoms for peace'), get_artist_audio_features)
non_studio_albums <- c('OK Computer OKNOTOK 1997 2017', 'TKOL RMX 1234567', 'In Rainbows Disk 2', 
                       'Com Lag: 2+2=5', 'I Might Be Wrong', 'The Eraser Rmxs')

tots <- filter(tots, !album_name %in% non_studio_albums)

album_names_label <- tots %>% 
    arrange(album_release_date) %>% 
    mutate(label = str_glue('{album_name} ({year(album_release_year)})')) %>% 
    pull(label) %>% 

plot_df <- tots %>% 
    select(track_name, album_name, danceability, album_release_date) %>% 
    gather(metric, value, -c(track_name, album_name, album_release_date))

p <- ggplot(plot_df, aes(x = value, y = album_release_date)) + 
    geom_density_ridges(size = .1) +
    theme_ridges(center_axis_labels = TRUE, grid = FALSE, font_size = 6) +
    theme(plot.title = element_text(face = 'bold', size = 14, hjust = 1.25),
          plot.subtitle = element_text(size = 10, hjust = 1.1)) +
    ggtitle('Have we reached peak Thom Yorke danceability?', 'Song danceability by album - Radiohead, Thom Yorke, and Atoms for Peace') +
    labs(x = 'Song danceability', y = '') +
    scale_x_continuous(breaks = c(0,.25,.5,.75,1)) +
    scale_y_discrete(labels = album_names_label)

ggsave(p, filename = 'img/danceplot.png', width = 5, height = 3)
#> Picking joint bandwidth of 0.0714
background <- image_read('img/danceplot.png')
logo_raw <- image_read('img/thom_dance.gif')
frames <- lapply(1:length(logo_raw), function(frame) {
    hjust <- 200+(100*frame)
    image_composite(background, logo_raw[frame], offset = str_glue('+{hjust}+400'))

image_animate(image_join(frames), fps = 5, loop = 0)


By default, get_artist_audio_features(), get_artist_albums(), get_album_tracks(), get_playlist_tracks(), and get_user_playlists() will run in parallel using the furrr package. To turn this feature off, set parallelize = FALSE. You can also adjust the evaluation strategy by setting future_plan, which accepts a string matching one of the strategies implemented in future::plan() (defaults to "multiprocess").

Sentify: A Shiny app

This app, powered by spotifyr, allows you to visualize the energy and valence (musical positivity) of all of Spotify's artists and playlists.

Dope stuff other people have done with spotifyr

The coolest thing about making this package has definitely been seeing all the awesome stuff other people have done with it. Here are a few examples:

Sentiment analysis of musical taste: a cross-European comparison - Paul Elvers

Blue Christmas: A data-driven search for the most depressing Christmas song - Caitlin Hudon

KendRick LamaR - David K. Laing

Vilken är Kents mest deprimerande låt? (What is Kent's most depressing song?) - Filip Wästberg

Чёрное зеркало Arcade Fire (Black Mirror Arcade Fire) - TheSociety

Sente-se triste quando ouve "Amar pelos dois"? Não é o único (Do you feel sad when you hear "Love for both?" You're not alone) - Rui Barros, Renascença

Hierarchical clustering of David Bowie records - Alyssa Goldberg