Crates.io | web-audio-api |
lib.rs | web-audio-api |
version | 1.0.1 |
source | src |
created_at | 2021-01-25 19:08:59.441881 |
updated_at | 2024-09-18 06:51:10.722382 |
description | A pure Rust implementation of the Web Audio API, for use in non-browser contexts |
homepage | |
repository | https://github.com/orottier/web-audio-api-rs |
max_upload_size | |
id | 346584 |
size | 1,895,406 |
A pure Rust implementation of the Web Audio API, for use in non-browser contexts
The Web Audio API (MDN docs) provides a powerful and versatile system for controlling audio on the Web, allowing developers to choose audio sources, add effects to audio, create audio visualizations, apply spatial effects (such as panning) and much more.
Our Rust implementation decouples the Web Audio API from the Web. You can now use it in desktop apps, command line utilities, headless execution, etc.
use web_audio_api::context::{AudioContext, BaseAudioContext};
use web_audio_api::node::{AudioNode, AudioScheduledSourceNode};
// set up the audio context with optimized settings for your hardware
let context = AudioContext::default();
// for background music, read from local file
let file = std::fs::File::open("samples/major-scale.ogg").unwrap();
let buffer = context.decode_audio_data_sync(file).unwrap();
// setup an AudioBufferSourceNode
let mut src = context.create_buffer_source();
src.set_buffer(buffer);
src.set_loop(true);
// create a biquad filter
let biquad = context.create_biquad_filter();
biquad.frequency().set_value(125.);
// connect the audio nodes
src.connect(&biquad);
biquad.connect(&context.destination());
// play the buffer
src.start();
// enjoy listening
std::thread::sleep(std::time::Duration::from_secs(4));
Check out the docs for more info.
We have tried to stick to the official W3C spec as close as possible, but some deviations could not be avoided:
We provide NodeJS bindings to this library over at https://github.com/ircam-ismm/node-web-audio-api so you can use this library by simply writing native NodeJS code.
This enables us to run the official WebAudioAPI test harness and track our spec compliance score.
By default, the cpal
library is used for
cross platform audio I/O.
We offer experimental support for the
cubeb
backend via the cubeb
feature
flag. Please note that cmake
must be installed locally in order to run
cubeb
.
Feature flag | Backends |
---|---|
cpal (default) | ALSA, WASAPI, CoreAudio, Oboe (Android) |
cpal-jack | JACK |
cpal-asio | ASIO see https://github.com/rustaudio/cpal#asio-on-windows |
cubeb | PulseAudio, AudioUnit, WASAPI, OpenSL, AAudio, sndio, Sun, OSS |
Using the library on Linux with the ALSA backend might lead to unexpected
cranky sound with the default render size (i.e. 128 frames). In such cases, a
simple workaround is to pass the AudioContextLatencyCategory::Playback
latency hint when creating the audio context, which will increase the render
size to 1024 frames:
let audio_context = AudioContext::new(AudioContextOptions {
latency_hint: AudioContextLatencyCategory::Playback,
..AudioContextOptions::default()
});
For real-time and interactive applications where low latency is crucial, you
should instead rely on the JACK backend provided by cpal
. To that end you
will need a running JACK server and build your application with the cpal-jack
feature, e.g. cargo run --release --features "cpal-jack" --example microphone
.
We can go full circle and pipe the Rust WebAudio output back into the browser
via cpal
's wasm-bindgen
backend. Check out an example WASM
project.
Warning: experimental!
web-audio-api-rs welcomes contribution from everyone in the form of suggestions, bug reports, pull requests, and feedback. 💛
If you need ideas for contribution, there are several ways to get started:
examples/
directory) and start
building your own audio graphsUnless you explicitly state otherwise, any contribution intentionally submitted for inclusion in web-audio-api-rs by you, shall be licensed as MIT, without any additional terms or conditions.
This project is licensed under the MIT license.
The IR files used for HRTF spatialization are part of the LISTEN database created by the EAC team from Ircam.