Skip to main content

A Python library for adding effects to audio.

Project description

Pedalboard Logo

License: GPL v3 Documentation PyPI - Python Version Supported Platforms Apple Silicon support for macOS and Linux (Docker) PyPI - Wheel Test Badge Coverage Badge PyPI - Downloads GitHub Repo stars

pedalboard is a Python library for working with audio: reading, writing, adding effects, and more. It supports most popular audio file formats and a number of common audio effects out of the box, and also allows the use of VST3® and Audio Unit formats for third-party plugins.

pedalboard was built by Spotify's Audio Intelligence Lab to enable using studio-quality audio effects from within Python and TensorFlow. Internally at Spotify, pedalboard is used for data augmentation to improve machine learning models. pedalboard also helps in the process of content creation, making it possible to add effects to audio without using a Digital Audio Workstation.

Features

  • Built-in audio I/O utilities (pedalboard.io)
    • Support for reading and writing AIFF, FLAC, MP3, OGG, and WAV files on all platforms with no dependencies
    • Additional support for reading AAC, AC3, WMA, and other formats depending on platform
  • Built-in support for a number of basic audio transformations, including:
    • Guitar-style effects: Chorus, Distortion, Phaser
    • Loudness and dynamic range effects: Compressor, Gain, Limiter
    • Equalizers and filters: HighpassFilter, LadderFilter, LowpassFilter
    • Spatial effects: Convolution, Delay, Reverb
    • Pitch effects: PitchShift
    • Lossy compression: GSMFullRateCompressor, MP3Compressor
    • Quality reduction: Resample, Bitcrush
  • Supports VST3® plugins on macOS, Windows, and Linux (pedalboard.load_plugin)
  • Supports Audio Units on macOS
  • Strong thread-safety, memory usage, and speed guarantees
    • Releases Python's Global Interpreter Lock (GIL) to allow use of multiple CPU cores
      • No need to use multiprocessing!
    • Even when only using one thread:
      • Processes audio up to 300x faster than pySoX for single transforms, and 2-5x faster than SoxBindings (via iCorv)
      • Reads audio files up to 4x faster than librosa.load (in many cases)
  • Tested compatibility with TensorFlow - can be used in tf.data pipelines!

Installation

pedalboard is available via PyPI (via Platform Wheels):

pip install pedalboard  # That's it! No other dependencies required.

If you are new to Python, follow INSTALLATION.md for a robust guide.

Compatibility

pedalboard is thoroughly tested with Python 3.6, 3.7, 3.8, 3.9, and 3.10 as well as experimental support for Python 3.11 and PyPy 3.7, 3.8, and 3.9.

  • Linux
    • Tested heavily in production use cases at Spotify
    • Tested automatically on GitHub with VSTs
    • Platform manylinux wheels built for x86_64 (Intel/AMD) and aarch64 (ARM/Apple Silicon)
    • Most Linux VSTs require a relatively modern Linux installation (with glibc > 2.27)
  • macOS
    • Tested manually with VSTs and Audio Units
    • Tested automatically on GitHub with VSTs
    • Platform wheels available for both Intel and Apple Silicon
    • Compatible with a wide range of VSTs and Audio Units
  • Windows
    • Tested automatically on GitHub with VSTs
    • Platform wheels available for amd64 (x86-64, Intel/AMD)

Examples

Quick start

from pedalboard import Pedalboard, Chorus, Reverb
from pedalboard.io import AudioFile

# Read in a whole audio file:
with AudioFile('some-file.wav', 'r') as f:
  audio = f.read(f.frames)
  samplerate = f.samplerate

# Make a Pedalboard object, containing multiple plugins:
board = Pedalboard([Chorus(), Reverb(room_size=0.25)])

# Run the audio through this pedalboard!
effected = board(audio, samplerate)

# Write the audio back as a wav file:
with AudioFile('processed-output.wav', 'w', samplerate, effected.shape[0]) as f:
  f.write(effected)

Making a guitar-style pedalboard

# Don't do import *! (It just makes this example smaller)
from pedalboard import *
from pedalboard.io import AudioFile

with AudioFile('guitar-input.wav', 'r') as f:
  audio = f.read(f.frames)
  samplerate = f.samplerate

# Make a pretty interesting sounding guitar pedalboard:
board = Pedalboard([
    Compressor(threshold_db=-50, ratio=25),
    Gain(gain_db=30),
    Chorus(),
    LadderFilter(mode=LadderFilter.Mode.HPF12, cutoff_hz=900),
    Phaser(),
    Convolution("./guitar_amp.wav", 1.0),
    Reverb(room_size=0.25),
])

# Pedalboard objects behave like lists, so you can add plugins:
board.append(Compressor(threshold_db=-25, ratio=10))
board.append(Gain(gain_db=10))
board.append(Limiter())

# ... or change parameters easily:
board[0].threshold_db = -40

# Run the audio through this pedalboard!
effected = board(audio, samplerate)

# Write the audio back as a wav file:
with AudioFile('processed-output.wav', 'w', samplerate, effected.shape[0]) as f:
  f.write(effected)

Using VST3® or Audio Unit plugins

from pedalboard import Pedalboard, Reverb, load_plugin
from pedalboard.io import AudioFile

# Load a VST3 or Audio Unit plugin from a known path on disk:
vst = load_plugin("./VSTs/RoughRider3.vst3")

print(vst.parameters.keys())
# dict_keys([
#   'sc_hpf_hz', 'input_lvl_db', 'sensitivity_db',
#   'ratio', 'attack_ms', 'release_ms', 'makeup_db',
#   'mix', 'output_lvl_db', 'sc_active',
#   'full_bandwidth', 'bypass', 'program',
# ])

# Set the "ratio" parameter to 15
vst.ratio = 15

# Use this VST to process some audio:
with AudioFile('some-file.wav', 'r') as f:
  audio = f.read(f.frames)
  samplerate = f.samplerate
effected = vst(audio, samplerate)

# ...or put this VST into a chain with other plugins:
board = Pedalboard([vst, Reverb()])
# ...and run that pedalboard with the same VST instance!
effected = board(audio, samplerate)

Creating parallel effects chains

This example creates a delayed pitch-shift effect by running multiple Pedalboards in parallel on the same audio. Pedalboard objects are themselves Plugin objects, so you can nest them as much as you like:

from pedalboard import Pedalboard, Compressor, Delay, Distortion, Gain, PitchShift, Reverb, Mix

passthrough = Gain(gain_db=0)

delay_and_pitch_shift = Pedalboard([
  Delay(delay_seconds=0.25, mix=1.0),
  PitchShift(semitones=7),
  Gain(gain_db=-3),
])

delay_longer_and_more_pitch_shift = Pedalboard([
  Delay(delay_seconds=0.5, mix=1.0),
  PitchShift(semitones=12),
  Gain(gain_db=-6),
])

board = Pedalboard([
  # Put a compressor at the front of the chain:
  Compressor(),
  # Run all of these pedalboards simultaneously with the Mix plugin:
  Mix([
    passthrough,
    delay_and_pitch_shift,
    delay_longer_and_more_pitch_shift,
  ]),
  # Add a reverb on the final mix:
  Reverb()
])

For more examples, see:

Contributing

Contributions to pedalboard are welcomed! See CONTRIBUTING.md for details.

License

pedalboard is Copyright 2021-2022 Spotify AB.

pedalboard is licensed under the GNU General Public License v3. pedalboard includes a number of libraries that are statically compiled, and which carry the following licenses:

VST is a registered trademark of Steinberg Media Technologies GmbH.

Project details


Download files

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

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

pedalboard-0.5.9-pp39-pypy39_pp73-win_amd64.whl (2.9 MB view details)

Uploaded PyPy Windows x86-64

pedalboard-0.5.9-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.1 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ x86-64

pedalboard-0.5.9-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (3.0 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ ARM64

pedalboard-0.5.9-pp39-pypy39_pp73-macosx_10_13_x86_64.whl (2.5 MB view details)

Uploaded PyPy macOS 10.13+ x86-64

pedalboard-0.5.9-pp38-pypy38_pp73-win_amd64.whl (2.9 MB view details)

Uploaded PyPy Windows x86-64

pedalboard-0.5.9-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.1 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ x86-64

pedalboard-0.5.9-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (3.0 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ ARM64

pedalboard-0.5.9-pp38-pypy38_pp73-macosx_10_13_x86_64.whl (2.5 MB view details)

Uploaded PyPy macOS 10.13+ x86-64

pedalboard-0.5.9-pp37-pypy37_pp73-win_amd64.whl (2.9 MB view details)

Uploaded PyPy Windows x86-64

pedalboard-0.5.9-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.1 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ x86-64

pedalboard-0.5.9-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (3.0 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ ARM64

pedalboard-0.5.9-pp37-pypy37_pp73-macosx_10_13_x86_64.whl (2.5 MB view details)

Uploaded PyPy macOS 10.13+ x86-64

pedalboard-0.5.9-cp310-cp310-win_amd64.whl (2.9 MB view details)

Uploaded CPython 3.10 Windows x86-64

pedalboard-0.5.9-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.1 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

pedalboard-0.5.9-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (3.0 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ ARM64

pedalboard-0.5.9-cp310-cp310-macosx_11_0_arm64.whl (2.3 MB view details)

Uploaded CPython 3.10 macOS 11.0+ ARM64

pedalboard-0.5.9-cp310-cp310-macosx_10_13_x86_64.whl (2.5 MB view details)

Uploaded CPython 3.10 macOS 10.13+ x86-64

pedalboard-0.5.9-cp310-cp310-macosx_10_13_universal2.whl (4.7 MB view details)

Uploaded CPython 3.10 macOS 10.13+ universal2 (ARM64, x86-64)

pedalboard-0.5.9-cp39-cp39-win_amd64.whl (2.9 MB view details)

Uploaded CPython 3.9 Windows x86-64

pedalboard-0.5.9-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.1 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

pedalboard-0.5.9-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (3.0 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ ARM64

pedalboard-0.5.9-cp39-cp39-macosx_11_0_arm64.whl (2.3 MB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

pedalboard-0.5.9-cp39-cp39-macosx_10_13_x86_64.whl (2.5 MB view details)

Uploaded CPython 3.9 macOS 10.13+ x86-64

pedalboard-0.5.9-cp39-cp39-macosx_10_13_universal2.whl (4.7 MB view details)

Uploaded CPython 3.9 macOS 10.13+ universal2 (ARM64, x86-64)

pedalboard-0.5.9-cp38-cp38-win_amd64.whl (2.9 MB view details)

Uploaded CPython 3.8 Windows x86-64

pedalboard-0.5.9-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.1 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

pedalboard-0.5.9-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (3.0 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ ARM64

pedalboard-0.5.9-cp38-cp38-macosx_11_0_arm64.whl (2.3 MB view details)

Uploaded CPython 3.8 macOS 11.0+ ARM64

pedalboard-0.5.9-cp38-cp38-macosx_10_13_x86_64.whl (2.5 MB view details)

Uploaded CPython 3.8 macOS 10.13+ x86-64

pedalboard-0.5.9-cp38-cp38-macosx_10_13_universal2.whl (4.7 MB view details)

Uploaded CPython 3.8 macOS 10.13+ universal2 (ARM64, x86-64)

pedalboard-0.5.9-cp37-cp37m-win_amd64.whl (2.9 MB view details)

Uploaded CPython 3.7m Windows x86-64

pedalboard-0.5.9-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.1 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ x86-64

pedalboard-0.5.9-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (3.1 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ ARM64

pedalboard-0.5.9-cp37-cp37m-macosx_10_13_x86_64.whl (2.5 MB view details)

Uploaded CPython 3.7m macOS 10.13+ x86-64

pedalboard-0.5.9-cp36-cp36m-win_amd64.whl (3.1 MB view details)

Uploaded CPython 3.6m Windows x86-64

pedalboard-0.5.9-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.1 MB view details)

Uploaded CPython 3.6m manylinux: glibc 2.17+ x86-64

pedalboard-0.5.9-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (3.1 MB view details)

Uploaded CPython 3.6m manylinux: glibc 2.17+ ARM64

pedalboard-0.5.9-cp36-cp36m-macosx_10_13_x86_64.whl (2.5 MB view details)

Uploaded CPython 3.6m macOS 10.13+ x86-64

File details

Details for the file pedalboard-0.5.9-pp39-pypy39_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-pp39-pypy39_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 a659784a45392918e7a47b9ad73f447c62188c2c74ce4e0d8cc34aed4299e4a3
MD5 d0a182a80cf3ae2d63f91ded53038e81
BLAKE2b-256 07b2d46c8977ebff116f2b71526be3d17818cd2ed7dba30b5cadec1643e2bde6

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.9-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 48466e67b1e6470f610c92d6e2672a5c0a775ed7606a4a45e57147c56c936984
MD5 eb4848d45f5a645a1650ec3af5c25cda
BLAKE2b-256 7847ed859f2bc56fdd46c5600e154cec38d847140c90e7b6c5728aa5b387e52e

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.9-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 a825127053ad067490186785432426e11cf208aec603c09f9de5a4b56c270318
MD5 9aa8ef77d8ecc32f4268fbd9ed7ab386
BLAKE2b-256 54b9c94f3a68fd7749ff66bf50e98ea5265c9466d48154f3829dabbfbf03915a

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.9-pp39-pypy39_pp73-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-pp39-pypy39_pp73-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 59cbec09f0625605a6ffc1a15c6685031d64a0a6effbfad34e813f7207101174
MD5 ad4fe714eb3a1ebfe73c854a9429e726
BLAKE2b-256 5d879f659a09c2bb389cc8a898abd1347294e300ce484729272b700578aa3e7b

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.9-pp38-pypy38_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-pp38-pypy38_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 609373cf6e896c39f8de704029a9134998e4a2ebb3c3094ef9ba1d502aa74755
MD5 c57c0ce0cedd5e0539bfb1b3a704d9b6
BLAKE2b-256 7425b1527f12b036b6dc280f21fc8ed7dcde8d32fe4ee1f550b10c71bb7bc7d7

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.9-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 69e4396004a83b5e2c6f35c0578368a263209a9b427c5f4899b6fb68c841f81f
MD5 11367904c3cecbd9164213797052e95d
BLAKE2b-256 26cea9234a211eda9084b68cf0f18ba9184141165c2aca191302f5651c1f85a3

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.9-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 8400c9ab8d5461eabdeee557ce50f45864e879129070b4dce3e92d0983b48559
MD5 37ac38c2e91d39651388684627ca0555
BLAKE2b-256 a348a2ff42d92cad01bc840cd684e7274f84cdf1ba2e633bd249829f312bb393

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.9-pp38-pypy38_pp73-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-pp38-pypy38_pp73-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 934ed18f26d57d8122a4bd41bad8ed888a0b9b80c4a47fbc9799204c784c0530
MD5 82e5f198ca4c848d6367c923481bbe9e
BLAKE2b-256 a15e14b2385f4043976df9660e0653f83d891b903b263bee3d74bef890234434

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.9-pp37-pypy37_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-pp37-pypy37_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 d0b2dafedc479a1a29632072e3533eb6bfff608717ec5b3e2beb75c16a6b7007
MD5 6e04795ab2a084c2d61b19974513b5e3
BLAKE2b-256 0530095cb439b26f28a61d79113c8f3c423d90e73989e5d6daaec05933eb896b

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.9-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 87f8ea03f8d9c09e82c85b03a0d652f580e6a96bc1b77c699adc8f3cb8da7e5a
MD5 cc86c353f233519e7cc2a2b6729af31c
BLAKE2b-256 46407908b8e0aeff4f2cd3e1ed7064cd63331fd41d722ce65a540545fe0a193e

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.9-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 5ca74fd273359d08c38bc2748f88dc1644db3bfbf2a47fd6a65c9de0ae51ac3f
MD5 d8742acdbe07c71468f7d686fc193016
BLAKE2b-256 e857d92438a3f70ce89476b10e95b22570a7b78fa0f9ff0b39e5e81146096c45

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.9-pp37-pypy37_pp73-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-pp37-pypy37_pp73-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 e24ceda6ccf994ebafea7ec6448d3b372d1a2c16a7fe24132309d8caa61addb3
MD5 0af4f60b8ece60b7cee805b4985394f4
BLAKE2b-256 5128038b962eaf50ac62e8d4d9f4e470c66b3076dc8b07690162c144b337d85c

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.9-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 d51fa5c84e7d42ebe416e7bb7f384a3ae5a941789157258c0aba3007d53b5165
MD5 4ad73d4634c8e04dd4991c54d8d8f4ee
BLAKE2b-256 e7f3111e239ae10089cc908368e9482a36e497973d8abf4e685cff3149cb8f03

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.9-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 52354e5640654991a01e6317a0441b0ac364e0001989590cf1a1b051e765f591
MD5 7d983b52922c3f9821f6cc3837fd50b0
BLAKE2b-256 5451cb0f7ba03b8eb0d2bda3e4fcba5bf28cd0362f4de564072186a0e578c9b9

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.9-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 752955aa66fd9402f832ebab7f50e5d59f7dc833a730bcd341aeb8f51b376a90
MD5 4c386bd168bd6bf503b2831359a60c31
BLAKE2b-256 2935556b6d0291006c73a98d075a4b5862c3ca9209f3bd9a877d3ae151ed4c90

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.9-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 d459be90590b135e4268583544a4bde124fddafbc7718d9914c5051aeb352ee2
MD5 ad5fb118bbe20a7ae5ddd9ea9c5a750f
BLAKE2b-256 502dbd2f4f041cb4a153141b5a62edfcfb0032050441e484185126722563a453

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.9-cp310-cp310-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-cp310-cp310-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 2bcc27501369fdacd214ecb196c1fda79db06d64c61f0f664a6517295e5f06f1
MD5 e841701f260c13bf1e18d777a8cd62e7
BLAKE2b-256 7bb217bd650fe77f123d42663f4773cacf81e9709f695609fcbe43e737d8d9ea

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.9-cp310-cp310-macosx_10_13_universal2.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-cp310-cp310-macosx_10_13_universal2.whl
Algorithm Hash digest
SHA256 d66f341c1ac7edf2eda294e4afa26ebd92065cb4320942aea2a385aabdd445fb
MD5 45f2159f5db5580dfd2e5606428cdce0
BLAKE2b-256 8ebc4e5aa22bde192f4c6d58626fa63908352c4c8784231d075ec2c3555c6bec

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.9-cp39-cp39-win_amd64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 b7d678eac1b202b4ddc5b75008c27f9029a0c59c899db98de2a0de1ea6c623bc
MD5 23df990cf96aae0585393e81909a5479
BLAKE2b-256 35d8d0ee84bdf00a96121c7a383422f605b595a2d0c7c19ffb6fc3b7d7cb8bae

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.9-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 c181feef09b3acc00f04bad08bb0f69875b2ffb294bf1d03dd0b0d2ccd3dec55
MD5 180091f52f212f298c344ac00cbe2e86
BLAKE2b-256 1f37e007e83f5ff71b52513ee3de5b6e53abe57cac3920826c6c5d6beb0bfb6d

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.9-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 cb38578780c9de02e6c37a5b17b61be03638dd981c82017c0b497bb60d34d677
MD5 2994ed8caf2b3e69635a8866d7b2f5c6
BLAKE2b-256 841fefddcdb65807fb130bc1c26a6bbdbe4aea2d716602d07fac2e6992ab3005

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.9-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 d8fadac5f53bca582a63beaa6f48c081b627ea32e499a200c1de749a262c34d5
MD5 fcd6bfcaa1c2592274e6bf5cdecb44ff
BLAKE2b-256 2f253fe95c950eb6a45b13556042e3647b8220ab9e5f20c816cc210532c8365a

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.9-cp39-cp39-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-cp39-cp39-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 412a8de8882f0288db49e8560096827f9b1885983830c3b653cc0ab914cdf558
MD5 78e26e0860f8cbe58704e24f7ffe8891
BLAKE2b-256 275a95350085e18bc0c3977e41856c5c736e6b804c84563ddaa619b9214830b6

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.9-cp39-cp39-macosx_10_13_universal2.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-cp39-cp39-macosx_10_13_universal2.whl
Algorithm Hash digest
SHA256 26b047131f54066f223850ea8bd0a1e07e5e2f31fe8545089451a52657d840f8
MD5 b16dce2ea3134f83dec950f5ddef66a4
BLAKE2b-256 58cc570eca06bf4cdf332bac9fc128000d4afb315ebb8f57344732eaa944e53a

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.9-cp38-cp38-win_amd64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 ce814db60b7236a6c75eadfbf4a5ee88e5cf6044e826f45f0ef9682f4c70181a
MD5 168592951f41a668c6126a8ad3250aa7
BLAKE2b-256 2de88b3268feacc3b9d7fb1303be0bcb10a817bd59aed57d8c73e81e46e2563d

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.9-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 cf90ca6b4e7a4a352f3bbaef88e8ab899d3668a716a25912d794f6bd5ded668c
MD5 529dbc605943d26fb0a65487b3727fbd
BLAKE2b-256 8fb8481db57fae7082573839d133b91039aa0ab92cd0ba8967c9d11d2aa07c55

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.9-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 3635fb2de32d37abeaa9396a038d05fa930e77b717fd09055bbe3c9ac1610c9c
MD5 54a1c84bfc98e0995564f2064e05b4e2
BLAKE2b-256 5dea408f2c9ace4926338301a8828bd658badaabfd86a11e0bef1184d502cf86

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.9-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 39b53dd5c0832ae105e6d7e30363b4220994e88dae7da540cbb554027240e2f7
MD5 d877f120a9fdf0efd5ec4e59fe1566a3
BLAKE2b-256 89a762de35c478c9c68c02b322210f0840b81d9741d3b7991ab260432409cf97

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.9-cp38-cp38-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-cp38-cp38-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 a5de078eb19bf601ff789d4e07c61ce1306cb2e52e55cedd4bf5ba2dca2d2703
MD5 29aead7dde1901c0f1fdc7c537bc3d8a
BLAKE2b-256 077115ee6224b3aa04b830634583cbfc27cd95cb811be7ad51758e9b54cf056a

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.9-cp38-cp38-macosx_10_13_universal2.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-cp38-cp38-macosx_10_13_universal2.whl
Algorithm Hash digest
SHA256 66ef63fe9b60ffd69d9e781d3c40333c3950ee5bd41537caeb0e66cf5c8aeba0
MD5 883de64389efe4228e0711c401340adf
BLAKE2b-256 5d8bd691aa522e010ae21ca5c7a7cbbd07dcb1e405c0465b127d54eca0b5cd57

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.9-cp37-cp37m-win_amd64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 0de2f80ed4241c7c3ffe0cda49915aa0ef9894cc154ba3490a00e74e4aa02df8
MD5 34de918649cda0ab177208cb8b09c205
BLAKE2b-256 ed8940a2d5ecbd847225bcb6c5f35c7e77740249cfd37da7c27c1f5107948ed9

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.9-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 3da2ebc176001ad3d27d5e06e1114a5a0decff48f02273d15fb0e54887706673
MD5 c7fb78f6a2128e94acb96f9eb136b20a
BLAKE2b-256 da4f8290c96aba8b0ff6e70eb20aa90e8b2b97803ea141dd3357b0d4a8f8bfca

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.9-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 e56f7f5642351d692221071f10f7605be10fc2653483e92914c299f14bf1fe2c
MD5 427eba65b36df526103d10aac066f395
BLAKE2b-256 5896e4f9a1936b509055498a73a35a1f4b5b9ea419180ddabd2f18f87a57655d

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.9-cp37-cp37m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-cp37-cp37m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 a7dce8212f9419192d6522e9ed0f001fa37d7fe4a52168613287e4e3d5473980
MD5 5b8b6b9bb6692d182e0e491582279c39
BLAKE2b-256 93229899e63b686b9c77d86caa8b6b82fd585858cd415fdf9b3345980089308f

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.9-cp36-cp36m-win_amd64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 92d1839b32b371acdc0c1cce80f8144587712d30ac39d323784c19d5d18a24d5
MD5 2ece361dd7a924b53ee465251e5c884c
BLAKE2b-256 37a4fd00792fa17a4fdaed289a1ff8ff9163a3434b71eb4ede93f89d2e98d61e

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.9-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 da8519cf875151ff156630e393c8e555638abe737b2fe355748fa08375f4282a
MD5 d7a468a7105fafc91d243f754d6e19dc
BLAKE2b-256 fe77690890e38f773fadcadb242b57f5e2242877f3201c2b89844489f3d8db70

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.9-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 8ee1b3413ce7917adf8354f5e58c6738c54f66525755a8bb11c16d85e15f7269
MD5 a68adc8968f07eefebb5b025d95fe762
BLAKE2b-256 02f9b9f0dee55fc0d3ccc4fee7fd773f4a836e88debe8c2ea031194239ca9390

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.9-cp36-cp36m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.9-cp36-cp36m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 19297744753b959c0efff70ab32dcb3d0e20c7890d7691bcf0205ce54f9a1f47
MD5 0dc399062394fc9ef84621a2275818cb
BLAKE2b-256 4ca3415d684f0c7455aa1ff51e30e7126faa4169491699ab96305973e46a2790

See more details on using hashes here.

Supported by

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