Examples#
Note: If you’d rather watch a video instead of reading examples or documentation, watch Working with Audio in Python (feat. Pedalboard) on YouTube.
Quick start#
from pedalboard import Pedalboard, Chorus, Reverb
from pedalboard.io import AudioFile
# Make a Pedalboard object, containing multiple audio plugins:
board = Pedalboard([Chorus(), Reverb(room_size=0.25)])
# Open an audio file for reading, just like a regular file:
with AudioFile('some-file.wav') as f:
# Open an audio file to write to:
with AudioFile('output.wav', 'w', f.samplerate, f.num_channels) as o:
# Read one second of audio at a time, until the file is empty:
while f.tell() < f.frames:
chunk = f.read(f.samplerate)
# Run the audio through our pedalboard:
effected = board(chunk, f.samplerate, reset=False)
# Write the output to our output file:
o.write(effected)
Note: For more information about how to process audio through Pedalboard plugins, including how the
reset
parameter works, see the documentation forpedalboard.Plugin.process
.
Making a guitar-style pedalboard#
# Don't do import *! (It just makes this example smaller)
from pedalboard import *
from pedalboard.io import AudioFile
# Read in a whole file, resampling to our desired sample rate:
samplerate = 44100.0
with AudioFile('guitar-input.wav').resampled_to(samplerate) as f:
audio = f.read(f.frames)
# 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 instrument and effect plugins#
from pedalboard import Pedalboard, Reverb, load_plugin
from pedalboard.io import AudioFile
from mido import Message # not part of Pedalboard, but convenient!
# Load a VST3 or Audio Unit plugin from a known path on disk:
instrument = load_plugin("./VSTs/Magical8BitPlug2.vst3")
effect = load_plugin("./VSTs/RoughRider3.vst3")
print(effect.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
effect.ratio = 15
# Render some audio by passing MIDI to an instrument:
sample_rate = 44100
audio = instrument(
[Message("note_on", note=60), Message("note_off", note=60, time=5)],
duration=5, # seconds
sample_rate=sample_rate,
)
# Apply effects to this audio:
effected = effect(audio, sample_rate)
# ...or put the effect into a chain with other plugins:
board = Pedalboard([effect, Reverb()])
# ...and run that pedalboard with the same VST instance!
effected = board(audio, sample_rate)
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()
])
Running Pedalboard on Live Audio#
pedalboard
supports streaming live audio through
an AudioStream
object,
allowing for real-time manipulation of audio by adding effects in Python.
from pedalboard import Pedalboard, Chorus, Compressor, Delay, Gain, Reverb, Phaser
from pedalboard.io import AudioStream
# Open up an audio stream:
with AudioStream(
input_device_name="Apogee Jam+", # Guitar interface
output_device_name="MacBook Pro Speakers"
) as stream:
# Audio is now streaming through this pedalboard and out of your speakers!
stream.plugins = Pedalboard([
Compressor(threshold_db=-50, ratio=25),
Gain(gain_db=30),
Chorus(),
Phaser(),
Convolution("./guitar_amp.wav", 1.0),
Reverb(room_size=0.25),
])
input("Press enter to stop streaming...")
# The live AudioStream is now closed, and audio has stopped.
Using Pedalboard in tf.data
Pipelines#
import tensorflow as tf
sr = 48000
# Put whatever plugins you like in here:
plugins = pedalboard.Pedalboard([pedalboard.Gain(), pedalboard.Reverb()])
# Make a dataset containing random noise:
# NOTE: for real training, here's where you'd want to load your audio somehow:
ds = tf.data.Dataset.from_tensor_slices([np.random.rand(sr)])
# Apply our Pedalboard instance to the tf.data Pipeline:
ds = ds.map(lambda audio: tf.numpy_function(plugins.process, [audio, sr], tf.float32))
# Create and train a (dummy) ML model on this audio:
model = tf.keras.models.Sequential([tf.keras.layers.InputLayer(input_shape=(sr,)), tf.keras.layers.Dense(1)])
model.compile(loss="mse")
model.fit(ds.map(lambda effected: (effected, 1)).batch(1), epochs=10)
For more examples, see: