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']

>>> Chord.from_tones("C", "E", "G").forte_number
'3-11'

>>> from pytheory.scales import Scale
>>> Scale.recommend("C", "Eb", "F", "Gb", "G", "Bb", top=3)
[('C', 'blues', 1.0), ...]

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 — with detune, stereo pan, and spread.

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. Stereo panned like a real kit.

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. Sidechain compression. Master bus compressor/limiter. Stereo output.

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 repl                            # interactive scratchpad
$ 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-0.34.1.tar.gz (131.3 kB view details)

Uploaded Source

Built Distribution

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

pytheory-0.34.1-py3-none-any.whl (134.0 kB view details)

Uploaded Python 3

File details

Details for the file pytheory-0.34.1.tar.gz.

File metadata

  • Download URL: pytheory-0.34.1.tar.gz
  • Upload date:
  • Size: 131.3 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-0.34.1.tar.gz
Algorithm Hash digest
SHA256 82e07ecf7fc96a7f6f90cb10c24271d2bd0081f18e0d34be74a38ca8de69a78a
MD5 8be15f41c7ce32c4d7edc31699cbab30
BLAKE2b-256 f6ea98590fb8479a5cab4a79d32a6b1abbccdcc7500c5bf679b1c5096c0d5862

See more details on using hashes here.

File details

Details for the file pytheory-0.34.1-py3-none-any.whl.

File metadata

  • Download URL: pytheory-0.34.1-py3-none-any.whl
  • Upload date:
  • Size: 134.0 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-0.34.1-py3-none-any.whl
Algorithm Hash digest
SHA256 84738dd792dd62308357003d6279ea6cd2738aa26059c2caa53831c30159bbd4
MD5 476b0f9d41c6fe99e3957cc51296d991
BLAKE2b-256 37664f1e6b635b411304b9c33d1c09f9b58061040062a2d789c566897cb5a52c

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