Skip to main content

Music Theory for Humans

Project description

PyTheory: Music Theory for Humans

Explore music theory, compose multi-part arrangements, and export to MIDI — all in Python.

$ pip install pytheory

Sketch Ideas Fast

from pytheory import Score, Pattern, Key, Duration, Chord
from pytheory.play import play_score

score = Score("4/4", bpm=140)
score.drums("bossa nova", repeats=4)

chords = score.part("chords", synth="fm", envelope="pad", reverb=0.4)
lead = score.part("lead", synth="saw", envelope="pluck", delay=0.3, lowpass=3000)
bass = score.part("bass", synth="sine", lowpass=500)

for sym in ["Am", "Dm", "E7", "Am"]:
    chords.add(Chord.from_symbol(sym), Duration.WHOLE)
    chords.add(Chord.from_symbol(sym), Duration.WHOLE)

lead.arpeggio("Am", bars=2, pattern="updown", octaves=2)
lead.arpeggio("Dm", bars=2, pattern="updown", octaves=2)
lead.set(lowpass=5000, reverb=0.4)
lead.arpeggio("E7", bars=2, pattern="up", octaves=2)
lead.arpeggio("Am", bars=2, pattern="updown", octaves=2)

for n in ["A2", "E2", "A2", "C3"] * 4:
    bass.add(n, Duration.QUARTER)

play_score(score)              # hear it now
score.save_midi("sketch.mid")  # open in your DAW

Hear It Instantly

$ pytheory demo

Music Theory

>>> from pytheory import Key, Chord, Tone

>>> Key("C", "major").chords
['C major', 'D minor', 'E minor', 'F major', 'G major', 'A minor', 'B diminished']

>>> [c.symbol for c in Key("G", "major").progression("I", "V", "vi", "IV")]
['G', 'D', 'Em', 'C']

>>> Chord.from_symbol("F#m7b5").identify()
'F# half-diminished 7th'

>>> Tone.from_string("C4").interval_to(Tone.from_string("G4"))
'perfect 5th'

>>> Key("C", "major").pivot_chords(Key("G", "major"))
['A minor', 'B minor', 'C major', 'D major', 'E minor', 'G major']

Composition

score = Score("4/4", bpm=124)
score.drums("house", repeats=16, fill="house", fill_every=8)

pad = score.part("pad", synth="supersaw", envelope="pad",
                 reverb=0.5, chorus=0.3, sidechain=0.85)
lead = score.part("lead", synth="saw", envelope="pluck",
                  legato=True, glide=0.03, humanize=0.3)
bass = score.part("bass", synth="sine", lowpass=300, sidechain=0.7)

# Song structure
score.section("verse")
# ... add notes ...
score.section("chorus")
lead.set(lowpass=5000, reverb=0.3)
# ... add notes ...
score.end_section()

score.repeat("verse")
score.repeat("chorus", times=2)

10 Synth Waveforms

sine, saw, triangle, square, pulse, FM, noise, supersaw, PWM slow, PWM fast

58 Drum Patterns

rock, jazz, bebop, bossa nova, salsa, samba, afrobeat, funk, reggae, house, trap, metal, drum and bass — and 45 more. Plus 21 fill presets.

6 Effects with Automation

lead = score.part("lead", synth="saw",
                  distortion=0.7, lowpass=1000, lowpass_q=5.0,
                  delay=0.3, reverb=0.4, reverb_type="plate",
                  chorus=0.3)

# Automate mid-song
lead.set(lowpass=4000, distortion=0.9)

# LFO modulation
lead.lfo("lowpass", rate=0.5, min=400, max=3000, bars=8)

Signal chain: distortion → chorus → lowpass → delay → reverb

Convolution Reverb

7 synthetic impulse responses: Taj Mahal (12s), cathedral, plate, spring, cave, parking garage, canyon.

pad = score.part("pad", synth="supersaw",
                 reverb=0.85, reverb_type="taj_mahal")

6 Musical Systems

Western, Indian (Hindustani), Arabic (Maqam), Japanese, Blues/Pentatonic, Javanese Gamelan — 40+ scales.

25 Instrument Presets

Guitar (8 tunings), bass, ukulele, mandolin family, violin family, banjo, harp, oud, sitar, erhu, and more — with chord fingering generation.

Command Line

$ pytheory demo                            # hear a generated track
$ pytheory key G major                     # explore a key
$ pytheory identify Cmaj7                  # analyze a chord symbol
$ pytheory progression C major I V vi IV   # build a progression
$ pytheory midi C major I V vi IV -o out.mid
$ pytheory play Am7 --synth saw --envelope pluck
$ pytheory modes C                         # show all modes
$ pytheory circle C                        # circle of fifths

Why Python?

A DAW is great for tweaking sounds. But when you're thinking about music — code is faster than clicking. Sketch ideas, hear them instantly, export MIDI, finish in your DAW.

Tools like Claude Code can use PyTheory to prototype musical ideas from natural language — "write a bossa nova in A minor with a saw lead and reverb" becomes real, playable music.

Documentation

pytheory.kennethreitz.org

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pytheory-0.25.7.tar.gz (89.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

pytheory-0.25.7-py3-none-any.whl (91.5 kB view details)

Uploaded Python 3

File details

Details for the file pytheory-0.25.7.tar.gz.

File metadata

  • Download URL: pytheory-0.25.7.tar.gz
  • Upload date:
  • Size: 89.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.10.8 {"installer":{"name":"uv","version":"0.10.8","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"macOS","version":null,"id":null,"libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":null}

File hashes

Hashes for pytheory-0.25.7.tar.gz
Algorithm Hash digest
SHA256 3a3de3dd16885110683aa1473ccb8093ddaee0d65802fa5670b760a10a92d97a
MD5 a7cfaeb7618dead75271e6d5023ca1b9
BLAKE2b-256 bdb55cf46ad94d643599766d1a72cabb25b9370ffe42c1fb26c42aa93163e863

See more details on using hashes here.

File details

Details for the file pytheory-0.25.7-py3-none-any.whl.

File metadata

  • Download URL: pytheory-0.25.7-py3-none-any.whl
  • Upload date:
  • Size: 91.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.10.8 {"installer":{"name":"uv","version":"0.10.8","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"macOS","version":null,"id":null,"libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":null}

File hashes

Hashes for pytheory-0.25.7-py3-none-any.whl
Algorithm Hash digest
SHA256 799541adb7e81a0f28a9a872170974d44f62fd204d0b03879ba8777f0197b009
MD5 5366286135daae0861f9ae589cb93953
BLAKE2b-256 68dc209d75add8c7ca026b955e119135cd444a20df5973a0703573632258093c

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page