Josiah Parry 2/12/2018
This package was created to provide an easy method to access lyrics as text data using the website Genius.
This package must be installed from GitHub.
devtools::install_github("josiahparry/geniusR")Load the package:
library(geniusR)## Loading required package: dplyr
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
suppressPackageStartupMessages(library(tidyverse)) # For manipulationgenius_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 nametrack_n: track numbertext: lyrics
emotions_math <- genius_album(artist = "Margaret Glaspy", album = "Emotions and Math")## Joining, by = c("track_title", "track_n", "track_url")
emotions_math## # A tibble: 372 x 4
## track_title track_n lyric line
## <chr> <int> <chr> <int>
## 1 Emotions And Math 1 Oh when I got you by my side 1
## 2 Emotions And Math 1 Everything's alright 2
## 3 Emotions And Math 1 Its just when your gone 3
## 4 Emotions And Math 1 I start to snooze the alarm 4
## 5 Emotions And Math 1 Cause I stay up until 4 in the morning 5
## 6 Emotions And Math 1 Counting all the days 'til you're back 6
## 7 Emotions And Math 1 Shivering in an ice cold bath 7
## 8 Emotions And Math 1 Of emotions and math 8
## 9 Emotions And Math 1 Oh it's a shame 9
## 10 Emotions And Math 1 And I'm to blame 10
## # ... with 362 more rows
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## # A tibble: 6 x 2
## artist album
## <chr> <chr>
## 1 Kendrick Lamar Section 80
## 2 Kendrick Lamar Good Kid, M.A.A.D City
## 3 Kendrick Lamar DAMN.
## 4 Sara Bareilles The Blessed Unrest
## 5 Sara Bareilles Kaleidoscope Heart
## 6 Sara Bareilles Little Voice
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))## Joining, by = c("track_title", "track_n", "track_url")
## Joining, by = c("track_title", "track_n", "track_url")
## Joining, by = c("track_title", "track_n", "track_url")
## Joining, by = c("track_title", "track_n", "track_url")
## Joining, by = c("track_title", "track_n", "track_url")
## Joining, by = c("track_title", "track_n", "track_url")
album_lyrics## # A tibble: 6 x 3
## artist album tracks
## <chr> <chr> <list>
## 1 Kendrick Lamar Section 80 <tibble [1,131 × 4]>
## 2 Kendrick Lamar Good Kid, M.A.A.D City <tibble [2,285 × 4]>
## 3 Kendrick Lamar DAMN. <tibble [1,116 × 4]>
## 4 Sara Bareilles The Blessed Unrest <tibble [698 × 4]>
## 5 Sara Bareilles Kaleidoscope Heart <tibble [565 × 4]>
## 6 Sara Bareilles Little Voice <tibble [586 × 4]>
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)## # A tibble: 6 x 6
## artist album track_title track_n lyric line
## <chr> <chr> <chr> <int> <chr> <int>
## 1 Sara Bare… The Blesse… Brave 1 You can be amazing 1
## 2 Sara Bare… The Blesse… Brave 1 You can turn a phrase … 2
## 3 Sara Bare… The Blesse… Brave 1 You can be the outcast 3
## 4 Sara Bare… The Blesse… Brave 1 Or be the backlash of … 4
## 5 Sara Bare… The Blesse… Brave 1 Or you can start speak… 5
## 6 Sara Bare… The Blesse… Brave 1 Nothing's gonna hurt y… 6
If you want only a single song, you can use genius_lyrics(). Supply an
artist and a song title as character strings, and
voila.
memory_street <- genius_lyrics(artist = "Margaret Glaspy", song = "Memory Street")
memory_street## # A tibble: 27 x 3
## track_title lyric line
## <chr> <chr> <int>
## 1 Memory Street Ring the alarm 1
## 2 Memory Street I'm on memory street 2
## 3 Memory Street With him on my arm 3
## 4 Memory Street And my feet on the dash of that car 4
## 5 Memory Street I don't dare 5
## 6 Memory Street Walk down memory street 6
## 7 Memory Street Why remember 7
## 8 Memory Street All the times I took forever to forget? 8
## 9 Memory Street Call the guards 9
## 10 Memory Street I'm at the gates 10
## # ... with 17 more rows
This returns a tibble with three columns title, text, and line.
However, you can specifiy additional arguments to control the amount of
information to be returned using the info argument.
info = "title"(default): Return the lyrics, line number, and song title.info = "simple": Return just the lyrics and line number.info = "artist": Return the lyrics, line number, and artist.info = "all": Return lyrics, line number, song title, artist.
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") ## # A tibble: 10 x 3
## track_title track_n track_url
## <chr> <int> <chr>
## 1 Whole 1 https://genius.com/Basement-whole-lyrics
## 2 Covet 2 https://genius.com/Basement-covet-lyrics
## 3 Spoiled 3 https://genius.com/Basement-spoiled-lyrics
## 4 Pine 4 https://genius.com/Basement-pine-lyrics
## 5 Bad Apple 5 https://genius.com/Basement-bad-apple-lyrics
## 6 Breathe 6 https://genius.com/Basement-breathe-lyrics
## 7 Control 7 https://genius.com/Basement-control-lyrics
## 8 Black 8 https://genius.com/Basement-black-lyrics
## 9 Comfort 9 https://genius.com/Basement-comfort-lyrics
## 10 Wish 10 https://genius.com/Basement-wish-lyrics
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(track_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_urlNow that we have the url, feed it into genius_url().
genius_url(piano_url, info = "simple")## # A tibble: 13 x 2
## lyric line
## <chr> <int>
## 1 No one knows me like the piano in my mother's home 1
## 2 You would show me I had something some people call a soul 2
## 3 And you dropped out the sky, oh you arrived when I was three yea… 3
## 4 No one knows me like the piano in my mother's home 4
## 5 You know I left, I flew the nest 5
## 6 And you know I won't be long 6
## 7 And in my chest you know me best 7
## 8 And you know I'll be back home 8
## 9 An angel by her side, all of the times I knew we couldn't cope 9
## 10 They said that it's her time, no tears in sight, I kept the feel… 10
## 11 And you took hold of me and never, never, never let me go 11
## 12 'Cause no one knows me like the piano in my mother's home 12
## 13 In my mother's home 13
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")## [1] "https://genius.com/Laura-Marling-Soothing-lyrics"
gen_album_url("Daniel Caesar", "Freudian")## [1] "https://genius.com/albums/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)
}As this is my first “package” there will be many issues. Please submit an issue and I will do my best to attend to it.
There are already issues of which I am present (the lack of error handling). If you would like to take those on, please go ahead and make a pull request. Please contact me on Twitter.