Skip to main content

Python wrapper around SoX.

Project description

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

Project details


Download files

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

Source Distribution

sox-1.5.0.tar.gz (63.9 kB view details)

Uploaded Source

File details

Details for the file sox-1.5.0.tar.gz.

File metadata

  • Download URL: sox-1.5.0.tar.gz
  • Upload date:
  • Size: 63.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.12.1

File hashes

Hashes for sox-1.5.0.tar.gz
Algorithm Hash digest
SHA256 12c7be5bb1f548d891fe11e82c08cf5f1a1d74e225298f60082e5aeb2469ada0
MD5 464e8913d5c8de9c497f7e1750c1fd17
BLAKE2b-256 3da2d8e0d8fd7abf509ead4a2cb0fb24e5758b5330166bf9223d5cb9f98a7e8d

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