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.
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:
pip install aiortcBuilding 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:
apt install libopus-dev libvpx-devOS X
On OS X run:
brew install opus libvpxLicense
aiortc is released under the BSD license.
Release files for aiortc 1.9.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| aiortc-1.9.0.tar.gz | 1.2 MB | Details |
Built distributions (wheels)
Total release size: 36.4 MB
Release files / aiortc-1.9.0.tar.gz
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Release files / aiortc-1.9.0-pp310-pypy310_pp73-win_amd64.whl
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Release files / aiortc-1.9.0-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
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No |
| Uploaded via |
twine/5.0.0 CPython/3.12.3
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Release files / aiortc-1.9.0-cp38-abi3-macosx_11_0_arm64.whl
| Download URL | aiortc-1.9.0-cp38-abi3-macosx_11_0_arm64.whl |
|---|---|
| Size | 896.0 kB |
| Tags | CPython 3.8 abi3 macOS 11.0+ ARM64 |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.0.0 CPython/3.12.3
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Release files / aiortc-1.9.0-cp38-abi3-macosx_10_9_x86_64.whl
| Download URL | aiortc-1.9.0-cp38-abi3-macosx_10_9_x86_64.whl |
|---|---|
| Size | 1.2 MB |
| Tags | CPython 3.8 abi3 macOS 10.9+ x86-64 |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.0.0 CPython/3.12.3
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