mediasoup-client-aiortc
mediasoup-client handler for aiortc Python library. Suitable for building Node.js applications that connect to a mediasoup server using WebRTC and exchange real audio, video and DataChannel messages with it in both directions.
Requirements
This module uses aiortc Python library, which requires Python 3. Check the installation requirements of aiortc in the project site.
Installation
Once the requirements above are satisfied, install mediasoup-client-aiortc within your Node.js application:
$ npm install --save mediasoup-client-aiortc
The "postinstall" script in package.json
will install the Python libraries (including aiortc) by using pip3
command. If such a command is not in the PATH
or has a different name in your system, you can override its location by setting the PIP
environment variable:
$ PIP=/home/me/bin/pip3 npm install --save mediasoup-client-aiortc
Once you run your Node.js application, mediasoup-client-aiortc will eventually spawn Python processes and communicate with them via UnixSocket
. This module assumes that there is a python3
executable in your PATH
to spawn the Python executable. If not, you can override its location by setting the PYTHON
environment variable:
$ PYTHON=/home/me/bin/python3.12 node my_app.js
API
// ES6 style.
import {
createWorker,
Worker,
WorkerSettings,
WorkerLogLevel,
AiortcMediaStream,
AiortcMediaStreamConstraints,
AiortcMediaTrackConstraints
} from "mediasoup-client-aiortc";
// CommonJS style.
const {
createWorker,
Worker,
WorkerSettings,
WorkerLogLevel,
AiortcMediaStream,
AiortcMediaStreamConstraints,
AiortcMediaTrackConstraints
} = require("mediasoup-client-aiortc");
async createWorker(settings: WorkerSettings)
function
Creates a mediasoup-client-aiortc Worker
instance. Each Worker
spawns and manages a Python subprocess.
@async
@returns
Worker
const worker = await createWorker({
logLevel: "warn"
});
Worker
class
The Worker
class. It represents a separate Python subprocess that can provide the Node.js application with audio/video tracks and mediasoup-client handlers
.
worker.pid
getter
The Python subprocess PID.
@type
String, read only
worker.closed
getter
Whether the subprocess is closed.
@type
Boolean, read only
worker.close()
method
Closes the subprocess and all its open resources (such as audio/video tracks and mediasoup-client handlers).
async worker.getUserMedia(constraints: AiortcMediaStreamConstraints)
method
Mimics the navigator.getUserMedia()
API. It creates an AiortcMediaStream
instance containing audio and/or video tracks. Those tracks can point to different sources such as device microphone, webcam, multimedia files or HTTP streams.
@async
@returns
AiortcMediaStream
const stream = await getUserMedia(
{
audio: true,
video: {
source: "file",
file: "file:///home/foo/media/foo.mp4"
}
});
const audioTrack = stream.getAudioTracks()[0];
const videoTrack = stream.getVideoTracks()[0];
async worker.createHandlerFactory()
method
Creates a mediasoup-client handler factory, suitable for the handlerFactory argument when instantiating a mediasoup-client Device.
@async
@returns
HandlerFactory
const device = new mediasoupClient.Device({
handlerFactory: worker.createHandlerFactory()
});
Note that all Python resources (such as audio/video) used within the Device
must be obtained from the same mediasoup-client-aiortc Worker
instance.
worker.on("died", fn(error: Error)
event
Emitted if the subprocess abruptly dies. This should not happen. If it happens there is a bug in the Python component.
WorkerSettings
type
type WorkerSettings =
{
/**
* Logging level for logs generated by the Python subprocess.
*/
logLevel?: WorkerLogLevel; // If unset it defaults to "error".
}
WorkerLogLevel
type
type WorkerLogLevel = "debug" | "warn" | "error" | "none";
Logs generated by both, Node.js and Python components of this module, are printed using the mediasoup-client debugging system with "mediasoup-client-aiortc" prefix/namespace.
AiortcMediaStream
class
A custom implementation of the W3C MediaStream class. An instance of AiortcMediaStream
is generated by calling worker.getUserMedia()
.
Audio and video tracks within an AiortcMediaStream
are instances of FakeMediaStreamTrack and reference "native" MediaStreamTracks
in the Python subprocess (handled by aiortc
library).
AiortcMediaStreamConstraints
type
The argument given to worker.getUserMedia()
.
type AiortcMediaStreamConstraints =
{
audio?: AiortcMediaTrackConstraints | boolean;
video?: AiortcMediaTrackConstraints | boolean;
}
Setting audio
or video
to true
equals to {source: "device"}
(so default microphone or webcam will be used to obtain the track or tracks).
AiortcMediaTrackConstraints
type
type AiortcMediaTrackConstraints =
{
source: "device" | "file" | "url";
device?: string;
file?: string;
url?: string;
format?: string;
options?: object;
timeout?: number;
loop?: boolean;
decode?: boolean;
}
source
Determines which source aiortc will use to generate the audio or video track. These are the possible values:
- "device": System microphone or webcam.
- "file": Path to a multimedia file in the system.
- "url": URL of an HTTP stream.
device
If source
is "device" and this field is given, it specifies the device ID of the microphone or webcam to use. If unset, the default one in the system will be used.
- Default values for
Darwin
platform:- "none:0" for audio.
- "default:none" for video.
- Default values for
Linux
platform:- "hw:0" for audio.
- "/dev/video0" for video.
file
Mandatory if source
is "file". Must be the absolute path to a multimedia file.
url
Mandatory if source
is "url". Must be the URL of an HTTP stream.
format
Specifies the device format used by ffmpeg
.
-
Default values for
Darwin
platform:- "avfoundation" for audio.
- "avfoundation" for video.
-
Default values for
Linux
platform:- "alsa" for audio.
- "v4f2" for video.
options
Specifies the device options used by ffmpeg
.
-
Default values for
Darwin
platform:-
{}
for audio. -
{ framerate: "30", video_size: "640x480" }
for video.
-
-
Default values for
Linux
platform:-
{}
for audio. -
{ framerate: "30", video_size: "640x480" }
for video.
-
timeout
, loop
and decode
See documentation in aiortc site (decode
option is not documented but you can figure it out by reading usage examples).
Other considerations
DataChannel
mediasoup-client-aiortc supports sending/receiving string and binary DataChannel messages. However, due to the lack of Blob
support in Node.js, dataChannel.binaryType
is always "arraybuffer" so received binary messages are always ArrayBuffer
instances.
When sending, dataChannel.send()
(and hence dataProducer.send()
) allows passing a string, a Buffer
instance or an ArrayBuffer
instance.
Development
Lint task
In order to run npm run lint
task, install Python dev dependencies:
$ npm run install-python-dev-deps
Make Python log to stdout/stderr while running tests
PYTHON_LOG_TO_STDOUT=true npm run test
Caveats
See the list of open issues.