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https://github.com/aiortc/aiortc

WebRTC and ORTC implementation for Python using asyncio
https://github.com/aiortc/aiortc

asyncio data-channel ortc python webrtc webrtc-libraries

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WebRTC and ORTC implementation for Python using asyncio

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README 

        
.. image:: docs/_static/aiortc.svg

   :width: 120px

   :alt: aiortc



.. image:: https://img.shields.io/pypi/l/aiortc.svg

   :target: https://pypi.python.org/pypi/aiortc

   :alt: License



.. image:: https://img.shields.io/pypi/v/aiortc.svg

   :target: https://pypi.python.org/pypi/aiortc

   :alt: Version



.. image:: https://img.shields.io/pypi/pyversions/aiortc.svg

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   :alt: Python versions



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   :alt: Tests



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   :target: https://aiortc.readthedocs.io/

   :alt: Documentation



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): https://webrtc.org/

.. _Object Real-Time Communication (ORTC): https://ortc.org/

.. _read the documentation: https://aiortc.readthedocs.io/en/latest/



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, with half-trickle and mDNS support

- 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



Installing

----------



The easiest way to install ``aiortc`` is to run:



.. code:: bash



    pip install aiortc



Building from source

--------------------



If there are no wheels for your system or if you wish to build aiortc from

source you will need a couple of libraries installed on your system:



- Opus for audio encoding / decoding

- LibVPX for video encoding / decoding



Linux

.....



On Debian/Ubuntu run:



.. code:: bash



    apt install libopus-dev libvpx-dev



OS X

....



On OS X run:



.. code:: bash



    brew install opus libvpx



License

-------



``aiortc`` is released under the `BSD license`_.



.. _BSD license: https://aiortc.readthedocs.io/en/latest/license.html