songleaf

Dense, readable one-page song sheets: lyrics and chords on one A4 page, with the lyrics as large as will fit.

pip install songleaf
python -m songleaf sheet "wonderwall oasis"    # -> a one-page PDF in ~/.local/share/songleaf/sheets/

The default source is the Kaggle chords-and-lyrics corpus (about 135,000 songs), read from a local copy of its zip (see Sources).

What the sheet looks like

• One page, largest type that fits. The lyric font size is found by search for each song. On 1,500 randomly sampled corpus songs, the median came out around 22 pt, and 1,498 of the 1,500 fit on one page. A song that cannot fit at the minimum size spills onto a second page.
• Chords take no line of their own. They are smaller and blue, start over the syllable they land on, and overlap the tops of the letters of their lyric line.
• Lines share rows. Consecutive lines of a paragraph are packed onto one row, separated by a light /. A blank line or a new section starts a new row.
• Small labels. Sections are grey prefixes (V1, Ch, Br); title, artist, capo and key are one small line at the top.

Command line

python -m songleaf search "wonderwall oasis"              # fuzzy: typos and word order don't matter
python -m songleaf search --artist oasis --lyrics "roads winding"
python -m songleaf sheet "wonderwall oasis" --output wonderwall.pdf
python -m songleaf sheet "wonderwall oasis" --pick 2      # the second-best match
python -m songleaf songs                                  # songs already stored
python -m songleaf sheet kaggle_chords:1234               # a song by its key: no search
python -m songleaf sheet kaggle_chords:1234 --refresh     # fetch it again from its source

The songleaf console script is the same command.

Python

import songleaf

hits = songleaf.search("wonderwall oasis")
song = songleaf.get_song(hits[0].key)  # a Song: lyrics text + annotations
songleaf.render_dense_a4(song, "wonderwall.pdf")  # {'font_size': ..., 'pages': 1, ...}

songleaf.sheet("wonderwall oasis")  # search, store and render in one call

The song model

A Song is lyrics text plus standoff annotations anchored on character offsets, so annotation layers never touch the text:

• section: spans its lines, {"label": "Chorus"};
• chord: a point on the first character of the syllable the chord lands on, {"symbol": "G/B", "timing": "at"} ("before" marks a chord that sounds ahead of that syllable);
• score: a link from a stretch of lyrics to a score snippet, {"source", "id", "url", "format"}.

Metadata (title, artist, capo, key) and provenance (source, id, url, licence) travel with the song, and Song.to_dict() is its JSON form.

from songleaf import Song, chord, section, parse_chords_over_lyrics

song = Song(
    "Paper boats drift", [section(0, 17, "Verse 1"), chord(0, "G"), chord(6, "D")]
)
song = parse_chords_over_lyrics(
    "G     D\nPaper boats drift"
)  # the same chords, from a chart

Storage

Songs are kept in a MutableMapping (songleaf.song_store()): one JSON file per song under ~/.local/share/songleaf/songs/. Rendered sheets go to ~/.local/share/songleaf/sheets/. Set SONGLEAF_DATA_DIR to move both.

Sources

KaggleChordsSource reads the chords-and-lyrics dataset through sung. It needs a local copy of the zip: point SUNG_CHORDS_AND_LYRICS_ZIP at it, or keep it where haggle downloads it ($HAGGLE_ROOTDIR/zips/eitanbentora/chords-and-lyrics-dataset.zip). Without a local copy, sung downloads it from Kaggle, which needs Kaggle credentials. The corpus was scraped from a chords site, so keep it to personal use.

Loading the corpus takes about five seconds on the first search in a process.

Extending

Three keyword arguments are the extension points, on sheet (and search for sources):

• sources=: objects with a name, search(query, *, title, artist, lyrics, limit) returning Hits, and get(song_id) returning a Song;
• store=: any MutableMapping[str, Song] (a dict works);
• renderer=: any (song, output) -> dict function.

songleaf.sheet("paper boats", sources=[my_source], store={}, renderer=my_renderer)