Install and load the package

devtools::install_github("josiahparry/geniusR")

Load the package:

library(geniusR)
library(tidyverse) # For manipulation

Whole Albums

genius_album() allows you to download the lyrics for an entire album in a tidy format. There are two arguments artists and album. Supply the quoted name of artist and the album (if it gives you issues check that you have the album name and artists as specified on Genius).

This returns a tidy data frame with three columns:

• title: track name
• track_n: track number
• text: lyrics

emotions_math <- genius_album(artist = "Margaret Glaspy", album = "Emotions and Math")
emotions_math

Multiple Albums

If you wish to download multiple albums from multiple artists, try and keep it tidy and avoid binding rows if you can. We can achieve this in a tidy workflow by creating a tibble with two columns: artist and album where each row is an artist and their album. We can then iterate over those columns with purrr:map2().

In this example I will extract 3 albums from Kendrick Lamar and Sara Bareilles (two of my favotire musicians). The first step is to create the tibble with artists and album titles.

albums <-  tibble(
  artist = c(
    rep("Kendrick Lamar", 3), 
    rep("Sara Bareilles", 3)
    ),
  album = c(
    "Section 80", "Good Kid, M.A.A.D City", "DAMN.",
    "The Blessed Unrest", "Kaleidoscope Heart", "Little Voice"
    )
)

albums

No we can iterate over each row using the map2 function. This allows us to feed each value from the artist and album columns to the genius_album() function. Utilizing a map call within a dplyr::mutate() function creates a list column where each value is a tibble with the data frame from genius_album(). We will later unnest this.

## We will have an additional artist column that will have to be dropped
album_lyrics <- albums %>% 
  mutate(tracks = map2(artist, album, genius_album))

album_lyrics

Now when you view this you will see that each value within the tracks column is <tibble>. This means that that value is infact another tibble. We expand this using tidyr::unnest().

# Unnest the lyrics to expand 
lyrics <- album_lyrics %>% 
  unnest(tracks) %>%    # Expanding the lyrics 
  arrange(desc(artist)) # Arranging by artist name 

head(lyrics)

Song Lyrics

DNA <- genius_lyrics(artist = "Kendrick Lamar", song = "DNA.")

DNA

Tracklists

genius_tracklist(), given an artist and an album will return a barebones tibble with the track title, track number, and the url to the lyrics.

genius_tracklist(artist = "Basement", album = "Colourmeinkindness") 

Nitty Gritty

genius_lyrics() generates a url to Genius which is fed to genius_url(), the function that does the heavy lifting of actually fetching lyrics.

I have not figured out all of the patterns that are used for generating the Genius.com urls, so errors are bound to happen. If genius_lyrics() returns an error. Try utilizing genius_tracklist() and genius_url() together to get the song lyrics.

For example, say “(No One Knows Me) Like the Piano” by Sampha wasn’t working in a standard genius_lyrics() call.

piano <- genius_lyrics("Sampha", "(No One Knows Me) Like the Piano")

We could grab the tracklist for the album Process which the song is from. We could then isolate the url for (No One Knows Me) Like the Piano and feed that into `genius_url().

# Get the tracklist for 
process <- genius_tracklist("Sampha", "Process")

# Filter down to find the individual song
piano_info <- process %>% 
  filter(title == "(No One Knows Me) Like the Piano")

# Filter song using string detection
# process %>% 
#  filter(stringr::str_detect(title, coll("Like the piano", ignore_case = TRUE)))

piano_url <- piano_info$track_url

Now that we have the url, feed it into genius_url().

genius_url(piano_url, info = "simple")

Generative functions

This package works almost entirely on pattern detection. The urls from Genius are (mostly) easily reproducible (shout out to Angela Li for pointing this out).

The two functions that generate urls are gen_song_url() and gen_album_url(). To see how the functions work, try feeding an artist and song title to gen_song_url() and an artist and album title to gen_album_url().

gen_song_url("Laura Marling", "Soothing")

gen_album_url("Daniel Caesar", "Freudian")

genius_lyrics() calls gen_song_url() and feeds the output to genius_url() which preforms the scraping.

Getting lyrics for albums is slightly more involved. It first calls genius_tracklist() which first calls gen_album_url() then using the handy package rvest scrapes the song titles, track numbers, and song lyric urls. Next, the song urls from the output are iterated over and fed to genius_url().

To make this more clear, take a look inside of genius_album()

genius_album <- function(artist = NULL, album = NULL, info = "simple") {

  # Obtain tracklist from genius_tracklist
  album <- genius_tracklist(artist, album) %>%

    # Iterate over the url to the song title
    mutate(lyrics = map(track_url, genius_url, info)) %>%

    # Unnest the tibble with lyrics
    unnest(lyrics) %>%
    
    # Deselect the track url
    select(-track_url)


  return(album)
}