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-0.39.3.tar.gz (158.0 kB view details)

Uploaded Source

Built Distribution

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

pytheory-0.39.3-py3-none-any.whl (161.0 kB view details)

Uploaded Python 3

File details

Details for the file pytheory-0.39.3.tar.gz.

File metadata

  • Download URL: pytheory-0.39.3.tar.gz
  • Upload date:
  • Size: 158.0 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-0.39.3.tar.gz
Algorithm Hash digest
SHA256 23d6f35058457b26a158484612bea748b0c3001df8c88521a3ec439a196f1233
MD5 ebfcf7d64412073934d6b6a9d1b93c30
BLAKE2b-256 2472e048abc9ab33d5606ebf76baa1f5d263a6b2fcee3d76eea6d80bc24df7f2

See more details on using hashes here.

File details

Details for the file pytheory-0.39.3-py3-none-any.whl.

File metadata

  • Download URL: pytheory-0.39.3-py3-none-any.whl
  • Upload date:
  • Size: 161.0 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-0.39.3-py3-none-any.whl
Algorithm Hash digest
SHA256 724e401bdb7fda3b4e602f940c1b6e6e71d50a6bf41296ed4bffb061c2395d31
MD5 d19db2b3ebe7d992013afa9418e362e2
BLAKE2b-256 1cec14c3e04def61ecf17bb53826d63b633187feeedf3fd60506ea4bc1052426

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