Hello there! Django 3.1 finally was released with support for Class Based Views and Function Based Views, a big thanks for this amazing gift to everyone at the Django Software Foundation.
So here is your quick-start guide on how to start writing asynchronous Django views.
This was a little tricky to get started with, I had to jumped over the process of how the support for async CBV was actually implemented. A good approach if you ask me, to maintain retro compatibility with normal sync requests/response, middleware and all cool features of Django that we all use and love.
Ba DjangoCon 2019 — Just Add Await: Retrofitting Async Into Django by Andrew Godwin which explains how asynchronicity in Django is been implemented, so lets create our first Async CBV.
Make sure to use latest Django version
$ pip install git+https://github.com/django/django.git@stable/3.1.x
The current async requests handlers need to check that you actually wrote an async views so to complain with this validation there two ways of doing so:
# 1. Add `_is_coroutine = asyncio.coroutines._is_coroutine` property to view.
That’s it, now whatever the implementation of your view might be (
post(), etc) it will be actually handle as an async one, lets add a
Please notice the async and await keywords you must add them in order to to indicate python to get ready and open a space in the event-loop (the thread in which async code runs) and send some awaited
call() to it, so when that awaited
Unfortunately, there is not yet support for async development server. So, we need the help of a cool guy called uvicorn checkout the logo is so cool!
$ pip install uvicorn
If you created your project with a modern version of Django you should have a settings file called:
asgi.py which basically complains with the ASGI specification. This file looks like magic, oh yeah!! but its just following a protocol of how to run ASGI application, in django the
get_asgi_application() function does all the heavy lifting creating a callable handler to run our Django app for us, This handler is invoked by Uvicorn passing the incoming request, so is the main entry point for our django app, similar as its predecessor WSGI. Ok lets gets our hands on it.
$ uvicorn project.asgi:application --reload
Uvicorn follows python module dot notation to access our
asgi.py, then the
: with the name of the handler in this case
application here is how my
asgi.py file looks like:
`djinar` is the name of my project.
Important thing to notice from this file is the
“DJANGO_SETTINGS_MODULE” environment variable which if not set, defaults to
“config.settings.local” which is the same as
config/settings/local.py my local development settings file, so two options here, your could
export DJANGO_SETTINGS_MODEL='your_project.settings' to point your settings.py or replace the default value at your asgi.py file before running Uvicorn, so it can find the correct settings file of your Django project.
Let’s make a test
POST request. I love this cli rest client called
httpie lets take it for a spin:
$ pip install httpie ... ... $ http POST localhost:8000 ... ...
Oh bummer we forgot to wire-in our view within the urls.py file.
lets give it an other try…
$ http POST http://localhost:8000/offer \# sleep should happen here, then eventually the response. ...This was run asynchronously, man thats a long word :|
Now try increasing/decreasing the
sleep() time on the async post view.
That was it! Now you know how to write Async CBV so create cool async applications that do not block the main thread of your application when running
io intensive e.g. long take DB queries, reading/writing to disk, sub reques/reponses inside a view, etc…
There is an other way of creating ACBVs …
# 2. Using `__call__`
At the time of writing this article I was not able to declare the async view in this way. My guess it that the actual support for this is work in progress, I will update this article once this is actually working on the stable branch, If you manage it to work in this way, drop me a line on twitter @brunuxcom
Lets go further and create an app for processing and stream live video from webcam using WebRTC technologies.
I adapted this from aiortc examples to run with Django, adding all the code here is going to make this post a little bit verbose, so I’m just review the Django related stuff instead, if you would like to run this code in your local, clone the repo:
$ git clone [email@example.com](mailto:firstname.lastname@example.org):Brunux/djnar.git --branch experiments
Check the README.md file for instruction on how to setup your local development environment.
So our streaming views should look like this:
We have one TempleView for serving, well, basically static content HTML/CSS/JS.
Magic happens on the
SteamingOfferView, more specific our
post() async function in which…
First, we read a posted RTC Session description (line 20) sent from the client check JS code, this is related to WebRTC Specification, with this description we can create a session between in this case two hosts, web browser client and our Django application, so in response to this session description we create an answer follwing WebRTC specifications (line 75) an send back to the client.
After this connection has been established the web browser client starts sending video over a
track channel (line 52) using this stream of video we apply a
VideoTransformTrack (line 60) using the selected transformation on the HTML page send over the
TemplateView, once it has been proccessed we send it back to the client, we also add some audio track to make it more fun (line 32).
Finally we open a data channel in which we ping →pong, back and forward over a data channel (data track) between the hosts.
As you can see the nature of this kind of communications is totally asynchronous and based on events, so this is a clear example of how we can take advantage of async class based views, processing video in real time and send the result to the client, I wonder what cool apps can we create applying OpenCV to the web.
Over here you can read about how to run sync code over async an other possible scenarios, this is very useful to make calls to the ORM from async code since currently there is no async support for it (at the time of writing is WIP), spoiler alert, you need to wrap your calls in this way:
from asgiref.sync import async\_to\_sync async def get\_data(...): ... sync\_get\_data = async\_to\_sync(get\_data) @async\_to\_sync async def get\_other\_data(...): ...
If your Django application contains, io intensive operations, rewriting only those io intensive views in an async way, it could help a lot with the performance, in the other hand if your app doesn’t actually have io at all, stay sync. Async could be complex and dangerous specially when mixing asyn with sync in different scenarios, so start sync then after applying all possible optimization start writing little pieces of async code until you reach the performance that you want.
Thanks for reading this article, if you enjoy it give it a clamp or drop me a line on twitter @brunuxcom have a great day! https://email@example.com/django-async-class-based-views-acbv-5986c4511ae6 https://firstname.lastname@example.org/django-async-class-based-views-acbv-5986c4511ae6