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3.8.7 • Public • Published


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.


This module uses aiortc Python library, which requires Python 3. Check the installation requirements of aiortc in the project site.


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


// ES6 style.
import {
} from "mediasoup-client-aiortc";

// CommonJS style.
const {
} = require("mediasoup-client-aiortc");

async createWorker(settings: WorkerSettings) function

Creates a mediasoup-client-aiortc Worker instance. Each Worker spawns and manages a Python subprocess.


@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. 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.


@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.


@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;


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.


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.


Mandatory if source is "file". Must be the absolute path to a multimedia file.


Mandatory if source is "url". Must be the URL of an HTTP stream.


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.


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


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.


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


See the list of open issues.







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