df_websockets 0.10.1

Websocket integration for Django

df_websockets

Based on django-channels and celery, df_websockets simplifies communication between clients and servers and processing tasks in background processes.

df_websockets is based on two main ideas:

• signals, that are functions triggered both on the server or the browser window by either the server or the client,
• topics to allow the server to send signals to any group of browser windows.

Signals are exchanged between the browser window and the server using a single websockets. Signals triggered by the browser on the server are processed as Celery tasks (so the websocket endpoint does almost nothing). Signals triggered by the server can be processed as other Celery tasks and as Javascript functions on the browser.

Requirements and installation

df_config works with:

• Python 3.6+,
• django 2.0+,
• celery 4.0+,
• redis,
• django-channels 2.0+,
• channels_redis.

You also need a working redis server and Celery setup.

python -m pip install df_websockets

In your settings, if you do not use df_config, you must add the following values:

ASGI_APPLICATION = "df_websockets.routing.application"
# the ASGI application to use with gunicorn or daphne
MIDDLEWARES = [..., "df_websockets.middleware.WebsocketMiddleware", ...]
# a required middleware
CELERY_APP = "df_websockets"
# the celery application
CELERY_DEFAULT_QUEUE = "celery"
# the default queue to use
WEBSOCKET_REDIS_CONNECTION = {'host': 'localhost', 'port': 6379, 'db': 3, 'password': ''}
WEBSOCKET_REDIS_EXPIRE = 36000
WEBSOCKET_REDIS_PREFIX = "ws"
WEBSOCKET_SIGNAL_DECODER = "json.JSONDecoder"
WEBSOCKET_SIGNAL_ENCODER = "django.core.serializers.json.DjangoJSONEncoder"
WEBSOCKET_TOPIC_SERIALIZER = "df_websockets.topics.serialize_topic"
WINDOW_INFO_MIDDLEWARES = ["df_websockets.ws_middleware.WindowKeyMiddleware", "df_websockets.ws_middleware.DjangoAuthMiddleware", "df_websockets.ws_middleware.Djangoi18nMiddleware", "df_websockets.ws_middleware.BrowserMiddleware",]
# equivalent to MIDDLEWARES, but for websockets
WEBSOCKET_URL = "/ws/"
# the endpoint for the websockets

If you use df_config and you use a local Redis, you have nothing to do: settings are automatically set and everything is working as soon as a Redis is running on your machine.

You can start a Celery worker and the development server:

python manage.py worker 
python manage.py runserver -Q celery,slow,fast

basic usage

A signal is a string attached to Python or Javascript functions. When this signal is triggered, all these functions are called. Of course, you can target the platforms on which the functions will be executed: the server (for Python code) or any set of browser windows.

First, we connect our code to the signal "myproject.first_signal".

from df_websockets.decorators import everyone, signal
import time

@signal(path="myproject.first_signal", is_allowed_to=everyone, queue="celery")
def my_first_signal(window_info, content=None):
    print(content)

@signal(path="myproject.first_signal", is_allowed_to=everyone, queue="slow")
def my_first_signal_slow(window_info, content=None):
    time.sleep(100)
    print(content)

/* static file "js/df_websockets.min.js" must be included first */
document.addEventListener("DOMContentLoaded", () => {
    window.DFSignals.connect('myproject.first_signal', (opts) => {
        console.warn(opts.content);
    });
});

Now, we can trigger this signal to call this functions. In both cases, both functions will be called on the server and in the browser window.

window.DFSignals.call('myproject.first_signal', {content: "Hello from browser"});

from df_websockets.tasks import WINDOW, trigger, SERVER
from df_websockets.decorators import everyone, signal
from django.http.response import HttpResponse

def any_view(request):  # this is a standard Django view
    trigger(request, 'myproject.first_signal', to=[SERVER, WINDOW], content="hello from a view")
    return HttpResponse()

@signal(path="myproject.second_signal", is_allowed_to=everyone, queue="slow")
def second_signal(window_info):
    trigger(window_info, 'myproject.first_signal', to=[SERVER, WINDOW], content="hello from Celery")

In this case, the to parameter targets both the server and the window.

topics

When the server triggers a signal, it can select if the signal is called on the server or on some browser windows.

A Django view using this signal system must call set_websocket_topics to add some ”topics” to this view. js/df_websockets.min.js must also be added to the resulting HTML.

from df_websockets.tasks import set_websocket_topics

def any_view(request):  # this is a standard Django view
    # useful code
    obj1 = MyModel.objects.get(id=42)
    set_websocket_topics(request, [obj1, obj2, obj3])
    return HttpResponse()

obj1, obj2, obj3 must be Python objects that are handled by the WEBSOCKET_TOPIC_SERIALIZER function. By default, any string and Django model are valid. Each window also has a unique identifier that is automatically added to this list, as well as the connected user id and the BROADCAST.

The following code will call the JS function on every browser window having the obj topic and to the displayed window.

from df_websockets.tasks import WINDOW, trigger
from df_websockets.tasks import set_websocket_topics

def another_view(request, obj_id):
    obj = MyModel.objects.get(id=42)
    trigger(request, 'myproject.first_signal', to=[WINDOW, obj], content="hello from a view")
    set_websocket_topics(request, [other_topics])
    return HttpResponse()

There are three special values:

• df_websockets.tasks.WINDOW: the original browser window,
• df_websockets.tasks.USER: all windows currently displayed by the connected user,
• df_websockets.tasks.BROADCAST: all windows currently active.

Some information about the original window (like its unique identifier or the connected user) must be provided to the triggered Python code, allowing it to trigger JS events on any selected window.
These data are stored in the WindowInfo object, automatically built from the HTTP request by the trigger function and provided as first argument to the triggered code. The trigger function accepts WindowInfo or HTTPRequest objects as first argument.

Testing signals

The signal framework requires a working Redis and a worker process. However, if you only want to check if a signal has been called in unitary tests, you can use :class:df_websockets.utils.SignalQueue. Both server-side and client-side signals are kept into memory:

• df_websockets.testing.SignalQueue.ws_signals,

  • keys are the serialized topics
  • values are lists of tuples (signal name, arguments as dict)

• df_websockets.testing.SignalQueue.python_signals

  • keys are the name of the queue

  • values are lists of (signal_name, window_info_dict, kwargs=None, from_client=False, serialized_client_topics=None, to_server=False, queue=None)

    • signal_name is … the name of the signal
    • window_info_dict is a WindowInfo serialized as a dict,
    • kwargs is a dict representing the signal arguments,
    • from_client is True if this signal has been emitted by a web browser,
    • serialized_client_topics is not None if this signal must be re-emitted to some client topics,
    • to_server is True if this signal must be processed server-side,
    • queue is the name of the selected Celery queue.

from df_websockets.tasks import trigger, SERVER
from df_websockets.window_info import WindowInfo
from df_websockets.testing import SignalQueue

from df_websockets.decorators import signal
# noinspection PyUnusedLocal
@signal(path='test.signal', queue='demo-queue')
def test_signal(window_info, value=None):
  print(value)

wi = WindowInfo()
with SignalQueue() as fd:
  trigger(wi, 'test.signal1', to=[SERVER, 1], value="value1")
  trigger(wi, 'test.signal2', to=[SERVER, 1], value="value2")

# fd.python_signals looks like {'demo-queue': [ ['test.signal1', {…}, {'value': 'value1'}, False, None, True, None], 
# # ['test.signal2', {…}, {'value': 'value2'}, False, None, True, None]]}
# fd.ws_signals looks like {'-int.1': [('test.signal1', {'value': 'value1'}), ('test.signal2', {'value': 'value2'})]}