transcription-and-notation-with-pytheory

Transcription & Notation

Getting music into PyTheory from audio/MIDI, and out to MIDI, sheet music, and tab.

Transcribe a recording → notes / MIDI

from pytheory import Score

score = Score.from_wav("hum.wav", bpm=80)        # estimates tempo if bpm omitted
for name, part in score.parts.items():
    print(name, len(part.notes), "notes")
score.save_midi("hum.mid")

• Score.from_wav(path, *, bpm=None, quantize=None, split=False, fmin=50, fmax=1500). quantize=0.25 snaps to sixteenths; split=True separates a full mix into bass + melody (and drums) instead of one monophonic melody part.
• .m4a/.mp3 work if afconvert/ffmpeg is available; WAV always works.
• CLI equivalent: pytheory transcribe hum.m4a out.mid (add --split, --quantize 0.25, --bpm 90).

Identify the chord in an audio buffer

from pytheory.audio import identify_chord
import scipy.io.wavfile
sr, data = scipy.io.wavfile.read("clip.wav")
identify_chord(data, sr)
# {'symbol': 'D7', 'confidence': 0.76, 'notes': ['D', 'F#', 'A', 'C']}  (or None)

Returns a best-guess symbol with a confidence (0..1) and the detected notes, or None if it can't tell. Works best on clean, sustained chords; it's a real-time recognizer, not a perfect oracle. (The live version is pytheory tune --chords, in the guitar skill.)

Import MIDI

from pytheory import Score
score = Score.from_midi("song.mid")

Export to every format

score.save_midi("song.mid")                                  # MIDI (drums ch 10)
open("song.abc", "w").write(score.to_abc(title="Song", key="C"))
open("song.xml", "w").write(score.to_musicxml(title="Song"))   # MusicXML for notation apps
open("song.ly",  "w").write(score.to_lilypond(title="Song", key="C"))
print(score.to_tab("part_name"))                             # ASCII guitar tab for a part

• to_tab(part_name, tuning="guitar", frets=24) turns a single part into tab.
• to_musicxml opens in MuseScore/Finale/Sibelius; to_lilypond engraves to PDF via LilyPond; to_abc is compact plain-text notation.