Skip to main content

data channel feature only version of aiortc which implements WebRTC and ORTC

Project description

this repo is special version of aiortc which can be install data channel feature only and it works on windows palatrom.

PRs is already requested. So this is tempolary repository.

Install procedure


pip install aiortc-dc

File transfer example of P2P direct communication over NAT (which can run on Windows platform!)




|rtd| |pypi-v| |pypi-pyversions| |pypi-l| |travis| |codecov| |gitter|

.. |rtd| image:: :target:

.. |pypi-v| image:: :target:

.. |pypi-pyversions| image:: :target:

.. |pypi-l| image:: :target:

.. |travis| image:: :target:

.. |codecov| image:: :target:

.. |gitter| image:: :target:

What is aiortc?

aiortc is a library for Web Real-Time Communication (WebRTC)_ and Object Real-Time Communication (ORTC)_ in Python. It is built on top of asyncio, Python's standard asynchronous I/O framework.

The API closely follows its Javascript counterpart while using pythonic constructs:

  • promises are replaced by coroutines
  • events are emitted using pyee.EventEmitter

To learn more about aiortc please read the documentation_.

.. _Web Real-Time Communication (WebRTC): .. _Object Real-Time Communication (ORTC): .. _read the documentation:

Why should I use aiortc?

The main WebRTC and ORTC implementations are either built into web browsers, or come in the form of native code. While they are extensively battle tested, their internals are complex and they do not provide Python bindings. Furthermore they are tightly coupled to a media stack, making it hard to plug in audio or video processing algorithms.

In contrast, the aiortc implementation is fairly simple and readable. As such it is a good starting point for programmers wishing to understand how WebRTC works or tinker with its internals. It is also easy to create innovative products by leveraging the extensive modules available in the Python ecosystem. For instance you can build a full server handling both signaling and data channels or apply computer vision algorithms to video frames using OpenCV.

Furthermore, a lot of effort has gone into writing an extensive test suite for the aiortc code to ensure best-in-class code quality.

Implementation status

aiortc allows you to exchange audio, video and data channels and interoperability is regularly tested against both Chrome and Firefox. Here are some of its features:

  • SDP generation / parsing
  • Interactive Connectivity Establishment, including half-trickle
  • DTLS key and certificate generation
  • DTLS handshake, encryption / decryption (for SCTP)
  • SRTP keying, encryption and decryption for RTP and RTCP
  • Pure Python SCTP implementation
  • Data Channels
  • Sending and receiving audio (Opus / PCMU / PCMA)
  • Sending and receiving video (VP8 / H.264)
  • Bundling audio / video / data channels
  • RTCP reports, including NACK / PLI to recover from packet loss


In addition to aiortc's Python dependencies you need a couple of libraries installed on your system for media codecs. FFmpeg 3.2 or greater is required.

On Debian/Ubuntu run:

.. code:: bash

apt install libavdevice-dev libavfilter-dev libopus-dev libvpx-dev pkg-config

On OS X run:

.. code:: bash

brew install ffmpeg opus libvpx pkg-config


aiortc is released under the BSD license_.

.. _BSD license:

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

aiortc-dc-0.5.5.tar.gz (1.1 MB view hashes)

Uploaded source

Built Distribution

aiortc_dc-0.5.5-py3-none-any.whl (69.5 kB view hashes)

Uploaded py3

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Huawei Huawei PSF Sponsor Microsoft Microsoft PSF Sponsor NVIDIA NVIDIA PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page