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-0.5.7-pp39-pypy39_pp73-win_amd64.whl (2.9 MB view details)

Uploaded PyPy Windows x86-64

pedalboard-0.5.7-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-0.5.7-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (3.0 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ ARM64

pedalboard-0.5.7-pp39-pypy39_pp73-macosx_10_13_x86_64.whl (2.5 MB view details)

Uploaded PyPy macOS 10.13+ x86-64

pedalboard-0.5.7-pp38-pypy38_pp73-win_amd64.whl (2.9 MB view details)

Uploaded PyPy Windows x86-64

pedalboard-0.5.7-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-0.5.7-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (3.0 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ ARM64

pedalboard-0.5.7-pp38-pypy38_pp73-macosx_10_13_x86_64.whl (2.5 MB view details)

Uploaded PyPy macOS 10.13+ x86-64

pedalboard-0.5.7-pp37-pypy37_pp73-win_amd64.whl (2.9 MB view details)

Uploaded PyPy Windows x86-64

pedalboard-0.5.7-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-0.5.7-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (3.0 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ ARM64

pedalboard-0.5.7-pp37-pypy37_pp73-macosx_10_13_x86_64.whl (2.5 MB view details)

Uploaded PyPy macOS 10.13+ x86-64

pedalboard-0.5.7-cp310-cp310-win_amd64.whl (2.9 MB view details)

Uploaded CPython 3.10 Windows x86-64

pedalboard-0.5.7-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-0.5.7-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (3.0 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ ARM64

pedalboard-0.5.7-cp310-cp310-macosx_11_0_arm64.whl (2.3 MB view details)

Uploaded CPython 3.10 macOS 11.0+ ARM64

pedalboard-0.5.7-cp310-cp310-macosx_10_13_x86_64.whl (2.5 MB view details)

Uploaded CPython 3.10 macOS 10.13+ x86-64

pedalboard-0.5.7-cp310-cp310-macosx_10_13_universal2.whl (4.7 MB view details)

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

pedalboard-0.5.7-cp39-cp39-win_amd64.whl (2.9 MB view details)

Uploaded CPython 3.9 Windows x86-64

pedalboard-0.5.7-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-0.5.7-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (3.0 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ ARM64

pedalboard-0.5.7-cp39-cp39-macosx_11_0_arm64.whl (2.3 MB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

pedalboard-0.5.7-cp39-cp39-macosx_10_13_x86_64.whl (2.5 MB view details)

Uploaded CPython 3.9 macOS 10.13+ x86-64

pedalboard-0.5.7-cp39-cp39-macosx_10_13_universal2.whl (4.7 MB view details)

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

pedalboard-0.5.7-cp38-cp38-win_amd64.whl (2.9 MB view details)

Uploaded CPython 3.8 Windows x86-64

pedalboard-0.5.7-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-0.5.7-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (3.0 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ ARM64

pedalboard-0.5.7-cp38-cp38-macosx_11_0_arm64.whl (2.3 MB view details)

Uploaded CPython 3.8 macOS 11.0+ ARM64

pedalboard-0.5.7-cp38-cp38-macosx_10_13_x86_64.whl (2.5 MB view details)

Uploaded CPython 3.8 macOS 10.13+ x86-64

pedalboard-0.5.7-cp38-cp38-macosx_10_13_universal2.whl (4.7 MB view details)

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

pedalboard-0.5.7-cp37-cp37m-win_amd64.whl (2.9 MB view details)

Uploaded CPython 3.7m Windows x86-64

pedalboard-0.5.7-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-0.5.7-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (3.1 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ ARM64

pedalboard-0.5.7-cp37-cp37m-macosx_10_13_x86_64.whl (2.5 MB view details)

Uploaded CPython 3.7m macOS 10.13+ x86-64

pedalboard-0.5.7-cp36-cp36m-win_amd64.whl (3.1 MB view details)

Uploaded CPython 3.6m Windows x86-64

pedalboard-0.5.7-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-0.5.7-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (3.1 MB view details)

Uploaded CPython 3.6m manylinux: glibc 2.17+ ARM64

pedalboard-0.5.7-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-0.5.7-pp39-pypy39_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-pp39-pypy39_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 87481175e20ad5ade29fe105ec9d587c45d5ff701dc377d779b7a90fb1be8da9
MD5 ac5b7a855f41da6c20345ee795e546d2
BLAKE2b-256 7675360816ed712c90e23852749c9a91b6c7698a7c85f43274fa6ce1eaf0d332

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.7-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 ea0aa4bdd0388a93fdccf9e9716a0676efedeb4bb9950ace6778803bb931a849
MD5 847920d653a3a73a09479cb14b59666d
BLAKE2b-256 3c24a8a9f1dc10f215c499d6cbd295a83a3b194e5c25d26363bb2d308b0cacbc

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.7-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 28d316421673de971a46b30b3119634f7f3e258e673a1227e76768e3a1eeb4c7
MD5 caf3ed21f9c37b3c399aa2336763c95a
BLAKE2b-256 9a7b745aa748870c919525cc9b04637535e8f28ba303f376d3e91fab47e5b3b4

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.7-pp39-pypy39_pp73-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-pp39-pypy39_pp73-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 9e72c8cdb6a9a44a0b7886f81f37c73322b9b9ef6a83692e7d2dca2f3ea4b7fc
MD5 160798c7c6873796f760a998c524d858
BLAKE2b-256 aa01ee1c2bd0ceb02f21bc6140ec83238e3fe1891452206bc3eecc8f24402469

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.7-pp38-pypy38_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-pp38-pypy38_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 356cefa5b42c84a1c8a642825128d1cbba50a0df0b23979a16f80b5ef72255fb
MD5 b83db9b02a21f83deee732f89bde33b0
BLAKE2b-256 73005b2c0dc0fcd0a53e29f4d772cd1b1aa5b321c90811f3092942e4110ca9ca

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.7-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 20e5917bfc26366acb07e64019b9084686abaf97b46e46596604f22eccc0fad8
MD5 79c1b53ce3b524e4f315b3f760f3d7f4
BLAKE2b-256 cc85bf84665edef55de2a837882582bee4a642214f6c42c1d71118bfad6da4b4

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.7-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 6204796751611939f08bb369a2ab950d35ffe7c9d22ea4192990a9cf2dccf671
MD5 07a636ca8c0a814c303a9beaa1e4ea85
BLAKE2b-256 c9788b5be08b325bd7076cfb79a908db55651950a971e2559449e5207771d650

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.7-pp38-pypy38_pp73-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-pp38-pypy38_pp73-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 09aa341c90b38c63bab1f51bc6485fbb23a1ee842ade6aa7ff3e3b92fc475325
MD5 db0a6a2e0f235dba90680cb566f3446e
BLAKE2b-256 3e9ceaa9a70d8d175f82912f6b693f0f7ad26e82b86df445a5960afdbc87e9ab

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.7-pp37-pypy37_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-pp37-pypy37_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 9e8969c5ab26f87a4d2e18c10fd75cbff5fd5aed4f78b73182daea8d4a2b5941
MD5 099571ec7b7b773705a14674f8450fdd
BLAKE2b-256 5fdc9dd44d968ea1ae500cd3a9c1cc695580b7a93168e24cd5d08cb8383184ad

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.7-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 f0fb3f1ebb4a271e35abc3e5c41292a70d4beb494381d5abbfaf10fb19039c70
MD5 319eac1340e3a2f0311ec4b972db56b3
BLAKE2b-256 0365a3461a315b83e3499f4e8cb889d91b245d92ecc231a6360bf5b8eca9124e

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.7-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 90d73f7a58eeb0ecab28de052f6c9f2427877012e18d1bcbddb1c55e493d9553
MD5 76c57573907a43c377c699fa3119a53d
BLAKE2b-256 dd3278addc08c8a6695440d5826c08b644c1f0f438f6aa16b863c5e8bc7a5c0e

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.7-pp37-pypy37_pp73-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-pp37-pypy37_pp73-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 bcb888f89a53999b2d032dba9730dd44a4c7cb40fe3eea86a0b5291a76497eea
MD5 d81cf942ae33e75998a150c720f794da
BLAKE2b-256 2d9b1fa9712fc8018fdc33d4716f124a9ec963b1b0d8bf1b4e1bf28e507d2b29

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.7-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 ab95556f31f17d509062f2ccc398bb3ad989e7ebcc59866b7350b4fa09ae27ed
MD5 1817acf4c350e1ab1179362d20e54c40
BLAKE2b-256 12f3feb0d64eb4c41024fc26304c02393a1b8b4051933f646809fdcf985d3a09

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.7-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 b92a50a9538ccc19d55ce3ab692f303f78a12857a7e9ec2505eed252ebdda89b
MD5 d4222ca94fd29fdf304a88a7c6f0bd6a
BLAKE2b-256 1b452392916ca5542797f13ff1f0fd5a2b8cd3d7c57fe445f4d3aab18de826f0

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.7-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 0a7fbb665f9202c5098a0d4eda9ff72c0e3552b0e58e6e33ae575a4cb2c0b58d
MD5 984221cb868fca372be07b57ed0bb294
BLAKE2b-256 01204c0efece0c96d177e1747be3854f22db926a1299424f3738d5b0ecda8aa3

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.7-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 a8c05679a82eb4e0a6a9a14c1acca9cc718f1f23474549aaeef49d6cf1e4f9eb
MD5 194245920b4a6f019e4ad847a8e5f0fd
BLAKE2b-256 5db2eec9399a842cc8ffaab6722f0a008fdd2d8d3ff135ea429c1b5362e1e8fe

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.7-cp310-cp310-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-cp310-cp310-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 f064a886aa2555040db9b713d5c85badfc90216987264818a934d11b22a929e5
MD5 5aec9fbd61ec640a682dde33c4ba4cb5
BLAKE2b-256 ff96b1032b618c17f39fb86749007ce348b01fa15b2652eb9429fe6cdb19ed1b

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.7-cp310-cp310-macosx_10_13_universal2.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-cp310-cp310-macosx_10_13_universal2.whl
Algorithm Hash digest
SHA256 b50cfc83036132e00a591732af47362c8afa7eeebef834d4281e0ed2c1063b3c
MD5 e8021dea58b26879de6752bc8df8013d
BLAKE2b-256 064abf6a23771bc419c717740169a6d0d0076e8f928a31cca46be40b5a95b4ac

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.7-cp39-cp39-win_amd64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 34084276fdd79c7906fbd00dbef9af7dadc38cc6e52b3171e08ced84c9607ce8
MD5 b940a7487f8f3bdd4d0de46a1a98d010
BLAKE2b-256 86a451d761e27375bb066f4462dfec7beb2569a6d2a42ddcd298a49db8f48b6d

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.7-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 356815e9c2e3346eec115274ffe58a17f1863e005d4121c3626dd6b111b373be
MD5 f7a6c90ea9ea21725b8f4328e8f5d6c3
BLAKE2b-256 6e4a2ca8ce91b97d62a5defe489d4429d65beefc41a1353b2920777e795c2657

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.7-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 067b67bb4999ef8efef6d098758b6e441e3cda07d2181219b2fe0543c6665fee
MD5 fa9f105443bc71b77accffbaaab16225
BLAKE2b-256 453d83550f6dae97067955122f4ff7893b2ffb3bbbff7e8ed43cae4b98795d1d

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.7-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 cf45d00b2c2f4e4fcf5c9b04be8253743a2834957dcb6cf0130fcc21ff9f180d
MD5 5015dc3214c0bf59b38d2035a3912bde
BLAKE2b-256 6e4179bb27c2d3c07db70cebcb124814e1d782bbf2dcf2c0ab1d50013a669f13

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.7-cp39-cp39-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-cp39-cp39-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 ec189a5fd42da5cbf22d4ac87c64a25e7a32cd4a34fd2626cc2669867b46d6f0
MD5 95ee37c64badef22b10be0fe1906f7c1
BLAKE2b-256 f196ad37d0822db99182acb48ca38f015a397220658f77a69874ec624c1d27ff

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.7-cp39-cp39-macosx_10_13_universal2.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-cp39-cp39-macosx_10_13_universal2.whl
Algorithm Hash digest
SHA256 9fe6bd86eefbcb333e723e643e7275ef2ce03d1592583ca3ddcd305e4928837c
MD5 d23412ebeb2f2f9b3771c687a0cf13fe
BLAKE2b-256 0f134b0b6ceceb8cdceb53773b999218f1ea0e95e8003e9f28d6992e088364aa

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.7-cp38-cp38-win_amd64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 0abd9bcb593067ac48bb6eb56e4027cb71a73d3c2d1ff7dbf670f698d8c58101
MD5 e59abb9288c9ba24af9867212ff86709
BLAKE2b-256 ddcdcd7fc9292fba5f9b1abdc19757f0f3cbd6273e5ea53fea2b894a1521a3f5

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.7-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 041816f8f7c0ba090ecf9fb59b20caacdfa5c8f9dda0429d7cc5258d5ce233db
MD5 8efb103f95a6c4c46242492b93b65015
BLAKE2b-256 fc0061b3f5bb837dcba3c821484546aa8c2f885404a8b632b846367c956acd5e

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.7-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 c175d3b6abe95cae482d33c5549834d8d9fb6cc3599a94ffb0bc28b74d3ecd0a
MD5 2baab19711cc65006edb85edb25f31f6
BLAKE2b-256 744e93fac5aa27a13b4a00743a1ded69671c03803b6e5d4f16d5b52a2f56d8cc

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.7-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 fbe625e776b1542c8a1d991e01211a7f403a290ee5f8929fa4af589c3e608237
MD5 328255bc7f343c27eaaf59e62fd5de15
BLAKE2b-256 49eadab42f40145f01c7065c1be0620695c8efd22782a461a924b78a07d4dbfa

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.7-cp38-cp38-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-cp38-cp38-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 10fb4843799777c66279701b35ff6e6493364038a031c968f5fb01f832a94f48
MD5 9e9538d30d7b906bd306bea9b7daeeb9
BLAKE2b-256 e520df5b236534f8199e6cd021b8fa9e63803b887437a9ad8cecaa564d233314

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.7-cp38-cp38-macosx_10_13_universal2.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-cp38-cp38-macosx_10_13_universal2.whl
Algorithm Hash digest
SHA256 ea279185f0bf545a95a1db69d35110da77fea02efcef3339470554de4b7f0603
MD5 a3f26ff5307444c19ff57bcd7bc257a1
BLAKE2b-256 d628fecfe5b1a161aaaf7cf97706daf07e20fbc6ee3573b7ab0209828c80f45d

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.7-cp37-cp37m-win_amd64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 f4b7a055dbf04d28f4507f931cf607132e2df2a9aac9eb77fb8b487d40979ebb
MD5 d2955bc388969d594a80b4d83dc41204
BLAKE2b-256 7c4de3c2b0d6183b7e46a763fa745ad17ae4e47142b81550ffca7c26f31749a5

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.7-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 99e8e20709e22d3698b62744f3cf1a782a3131c760bfee6772417056de0b8d66
MD5 774680f22f6edeabb6901611c6151ff3
BLAKE2b-256 b05566d99a4ec8a74c11a8ffec6683fb5888aef88df6853dd83e44b1e572b1a3

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.7-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 8a8823e028e36e35c5bcc4695f5aa757939a91d656c131a408fe247be053dd8f
MD5 3d5ad8c52e27040df9bc63b13b859f20
BLAKE2b-256 11930c3318cd9503c7f2ec97026e07e5fcf6fa8838000d6efd946c4ae9682424

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.7-cp37-cp37m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-cp37-cp37m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 2834f767d6804203dc137b509b6967c5e250a269e0c9e0847c6936a7c51d8577
MD5 f64b166de67634ebb9bae726b3e0137f
BLAKE2b-256 06ef3d108a6b91ec45aae255744ee969fa52c7cba86c40ea8cb2da6a8acd3270

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.7-cp36-cp36m-win_amd64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 960fc619ea40a2b2b3bbd9c03f1ca56e1871fae12e24cb295faa9bc5f4160ce4
MD5 ae9fe56aacedd2ae25f31c171e8f931a
BLAKE2b-256 ff8e9300d1629ddeadc8783ee89ea3ba301dd4e0b8439c48279e23662558d72b

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.7-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 979ef74e780a4f90ea340fdeeab059f6f30f6aa96537fadca90bd78c95e07656
MD5 c19c429675a6eda845f0d6888d2e0a1a
BLAKE2b-256 b1abdc48b77b16c4cc9ffbcdb30df6a0159f5dff46095b9e882236a1023af0c3

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.7-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 7f788ea90c81cb4340ca723a98b797e455e67d1e4f6e073bab42ef10149636e4
MD5 43add682ffa9d924e1498e637fc03789
BLAKE2b-256 d1d7477613d2e7a5d2bbb1cb931707eb70b3b00d84fde53e196457256910c241

See more details on using hashes here.

File details

Details for the file pedalboard-0.5.7-cp36-cp36m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for pedalboard-0.5.7-cp36-cp36m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 976debd90c4a27b23c802616b7135217ee0e6103db85f7a7cfa4d933be37119a
MD5 25aff41d1f4c75f58c8f4dff1bc1d626
BLAKE2b-256 48779949c1c9e4efe14a94638bea152430ee19ddbfc6f61f0063729019786ef4

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