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pysox

Python wrapper around sox. Read the Docs here.

PyPI version Documentation Status GitHub license PyPI

Build Status Coverage Status

PySocks

This library was presented in the following paper:

R. M. Bittner, E. J. Humphrey and J. P. Bello, "pysox: Leveraging the Audio Signal Processing Power of SoX in Python", in Proceedings of the 17th International Society for Music Information Retrieval Conference Late Breaking and Demo Papers, New York City, USA, Aug. 2016.

Install

This requires that SoX version 14.4.2 or higher is installed.

To install SoX on Mac with Homebrew:

brew install sox

If you want support for mp3, flac, or ogg files, add the following flags:

brew install sox --with-lame --with-flac --with-libvorbis

on Linux:

apt-get install sox

or install from source.

To install the most up-to-date release of this module via PyPi:

pip install sox

To install the master branch:

pip install git+https://github.com/rabitt/pysox.git

or

git clone https://github.com/rabitt/pysox.git
cd pysox
python setup.py install

Tests

If you have a different version of SoX installed, it's recommended that you run the tests locally to make sure everything behaves as expected, by simply running:

pytest

Examples

import sox
# create transformer
tfm = sox.Transformer()
# trim the audio between 5 and 10.5 seconds.
tfm.trim(5, 10.5)
# apply compression
tfm.compand()
# apply a fade in and fade out
tfm.fade(fade_in_len=1.0, fade_out_len=0.5)
# create an output file.
tfm.build_file('path/to/input_audio.wav', 'path/to/output/audio.aiff')
# or equivalently using the legacy API
tfm.build('path/to/input_audio.wav', 'path/to/output/audio.aiff')
# get the output in-memory as a numpy array
# by default the sample rate will be the same as the input file
array_out = tfm.build_array(input_filepath='path/to/input_audio.wav')
# see the applied effects
tfm.effects_log
> ['trim', 'compand', 'fade']

Transform in-memory arrays:

import numpy as np
import sox
# sample rate in Hz
sample_rate = 44100
# generate a 1-second sine tone at 440 Hz
y = np.sin(2 * np.pi * 440.0 * np.arange(sample_rate * 1.0) / sample_rate)
# create a transformer
tfm = sox.Transformer()
# shift the pitch up by 2 semitones
tfm.pitch(2)
# transform an in-memory array and return an array
y_out = tfm.build_array(input_array=y, sample_rate_in=sample_rate)
# instead, save output to a file
tfm.build_file(
    input_array=y, sample_rate_in=sample_rate,
    output_filepath='path/to/output.wav'
)
# create an output file with a different sample rate
tfm.set_output_format(rate=8000)
tfm.build_file(
    input_array=y, sample_rate_in=sample_rate,
    output_filepath='path/to/output_8k.wav'
)

Concatenate 3 audio files:

import sox
# create combiner
cbn = sox.Combiner()
# pitch shift combined audio up 3 semitones
cbn.pitch(3.0)
# convert output to 8000 Hz stereo
cbn.convert(samplerate=8000, n_channels=2)
# create the output file
cbn.build(
    ['input1.wav', 'input2.wav', 'input3.wav'], 'output.wav', 'concatenate'
)
# the combiner does not currently support array input/output

Get file information:

import sox
# get the sample rate
sample_rate = sox.file_info.sample_rate('path/to/file.mp3')
# get the number of samples
n_samples = sox.file_info.num_samples('path/to/file.wav')
# determine if a file is silent
is_silent = sox.file_info.silent('path/to/file.aiff')
# file info doesn't currently support array input