Mention RabbitMQ layer in the docs. (#608)

README.rst

@@ -29,7 +29,8 @@ Support can be obtained either here via issues, or in the ``#django-channels``
 channel on Freenode.
 
 You can install channels from PyPI as the ``channels`` package.
-You'll likely also want to ``asgi_redis`` to provide the Redis channel layer.
+You'll likely also want to install ``asgi_redis`` or ``asgi_rabbitmq``
+to provide the Redis/RabbitMQ channel layer correspondingly.
 See our `installation <https://channels.readthedocs.io/en/latest/installation.html>`_
 and `getting started <https://channels.readthedocs.io/en/latest/getting-started.html>`_ docs for more.
 
@@ -78,4 +79,5 @@ The Channels project is made up of several packages; the others are:
 * `Daphne <https://github.com/django/daphne/>`_, the HTTP and Websocket termination server
 * `asgiref <https://github.com/django/asgiref/>`_, the base ASGI library/memory backend
 * `asgi_redis <https://github.com/django/asgi_redis/>`_, the Redis channel backend
+* `asgi_rabbitmq <https://github.com/proofit404/asgi_rabbitmq/>`_, the RabbitMQ channel backend
 * `asgi_ipc <https://github.com/django/asgi_ipc/>`_, the POSIX IPC channel backend

channels/package_checks.py

@@ -3,6 +3,7 @@ from distutils.version import StrictVersion
 
 
 required_versions = {
+    "asgi_rabbitmq": "0.4.0",
     "asgi_redis": "1.2.0",
     "asgi_ipc": "1.3.0",
 }
@@ -21,7 +22,7 @@ def check_all():
         try:
             module = importlib.import_module(package)
         except ImportError:
-            return
+            continue
         else:
             if StrictVersion(version) > StrictVersion(module.__version__):
                 raise RuntimeError("Your version of %s is too old - it must be at least %s" % (

docs/backends.rst

@@ -54,6 +54,31 @@ the consistent hashing model relies on all running clients having the same
 settings. Any misconfigured interface server or worker will drop some or all
 messages.
 
+RabbitMQ
+--------
+
+RabbitMQ layer is comparable to Redis in terms of latency and
+throughput.  It can work with single RabbitMQ node and with Erlang
+cluster.
+
+You need to install layer package from PyPI::
+
+    pip install -U asgi_rabbitmq
+
+To use it you also need provide link to the virtual host with granted
+permissions::
+
+    CHANNEL_LAYERS = {
+        "default": {
+            "BACKEND": "asgi_rabbitmq.RabbitmqChannelLayer",
+            "ROUTING": "???",
+            "CONFIG": {
+                "url": "amqp://guest:guest@rabbitmq:5672/%2F",
+            },
+        },
+    }
+
+This layer has complete `documentation <http://asgi-rabbitmq.readthedocs.io/en/latest/>`_ on its own.
 
 IPC
 ---

docs/contributing.rst

@@ -22,6 +22,7 @@ of the Channels sub-projects:
  * `Daphne issues <https://github.com/django/daphne/issues/>`_, for the HTTP and Websocket termination
  * `asgiref issues <https://github.com/django/asgiref/issues/>`_, for the base ASGI library/memory backend
  * `asgi_redis issues <https://github.com/django/asgi_redis/issues/>`_, for the Redis channel backend
+ * `asgi_rabbitmq <https://github.com/proofit404/asgi_rabbitmq/>`_, for the RabbitMQ channel backend
  * `asgi_ipc issues <https://github.com/django/asgi_ipc/issues/>`_, for the POSIX IPC channel backend
 
 Issues are categorized by difficulty level:

docs/deploying.rst

@@ -79,6 +79,19 @@ Make sure the same settings file is used across all your workers and interface
 servers; without it, they won't be able to talk to each other and things
 will just fail to work.
 
+If you prefer to use RabbitMQ layer, please refer to its
+`documentation <http://asgi-rabbitmq.readthedocs.io/en/latest/>`_.
+Usually your config will end up like this::
+
+    CHANNEL_LAYERS = {
+        "default": {
+            "BACKEND": "asgi_rabbitmq.RabbitmqChannelLayer",
+            "ROUTING": "my_project.routing.channel_routing",
+            "CONFIG": {
+                "url": "amqp://guest:guest@rabbitmq:5672/%2F",
+            },
+        },
+    }
 
 Run worker servers
 ------------------

docs/index.rst

@@ -29,6 +29,7 @@ Channels is comprised of five packages:
 * `Daphne <https://github.com/django/daphne/>`_, the HTTP and Websocket termination server
 * `asgiref <https://github.com/django/asgiref/>`_, the base ASGI library/memory backend
 * `asgi_redis <https://github.com/django/asgi_redis/>`_, the Redis channel backend
+* `asgi_rabbitmq <https://github.com/proofit404/asgi_rabbitmq/>`_, the RabbitMQ channel backend
 * `asgi_ipc <https://github.com/django/asgi_ipc/>`_, the POSIX IPC channel backend
 
 This documentation covers the system as a whole; individual release notes and

loadtesting/2016-09-06/README.rst

@@ -1,5 +1,5 @@
 Django Channels Load Testing Results for (2016-09-06)
-===============
+=====================================================
 
 The goal of these load tests is to see how Channels performs with normal HTTP traffic under heavy load.
 
@@ -11,7 +11,7 @@ comparison to a WSGI HTTP server. Gunincorn was chosen as its configuration was
 
 
 Summary of Results
-~~~~~~~~~~~~
+~~~~~~~~~~~~~~~~~~
 
 Daphne is not as efficient as its WSGI counterpart. When considering only latency, Daphne can have 10 times the latency
 when under the same traffic load as gunincorn. When considering only throughput, Daphne can have 40-50% of the total
@@ -29,7 +29,7 @@ Some additional things that should be tested:
 
 
 Methodology
-~~~~~~~~~~~~
+~~~~~~~~~~~
 
 In order to control for variances, several measures were taken:
 
@@ -42,7 +42,7 @@ In order to control for variances, several measures were taken:
 
 
 Setups
-~~~~~~~~~~~~
+~~~~~~
 
 3 setups were used for this set of tests:
 
@@ -52,7 +52,7 @@ Setups
 
 
 Latency
-~~~~~~~~~~~~
+~~~~~~~
 
 All target and sources machines were identical ec2 instances m3.2xlarge running Ubuntu 16.04.
 
@@ -63,7 +63,7 @@ In order to ensure that the same number of requests were sent, the rps flag was
 
 
 Throughput
-~~~~~~~~~~~~
+~~~~~~~~~~
 
 The same source machine was used for all tests: ec2 instance m3.large running Ubuntu 16.04.
 All target machines were identical ec2 instances m3.2xlarge running Ubuntu 16.04.
@@ -77,7 +77,7 @@ Gunicorn had a latency of 6 ms; daphne and Redis, 12 ms; daphne and IPC,  35 ms.
 
 
 Supervisor Configs
-~~~~~~~~~~~~
+~~~~~~~~~~~~~~~~~~
 
 **Gunicorn (19.6.0)**
 
@@ -89,7 +89,7 @@ This is the non-channels config. It's a standard Django environment on one machi
   command = gunicorn testproject.wsgi_no_channels -b 0.0.0.0:80
   directory = /srv/channels/testproject/
   user = root
-  
+
   [group:django_http]
   programs=gunicorn
   priority=999
@@ -107,13 +107,13 @@ Also, it's a single worker, not multiple, as that's the default config.
   command = daphne -b 0.0.0.0 -p 80 testproject.asgi:channel_layer
   directory = /srv/channels/testproject/
   user = root
-  
+
   [program:worker]
   command = python manage.py runworker
   directory = /srv/channels/testproject/
   user = django-channels
-  
-  
+
+
   [group:django_channels]
   programs=daphne,worker
   priority=999
@@ -130,13 +130,13 @@ This is the channels config using IPC (Inter Process Communication). It's only p
   command = daphne -b 0.0.0.0 -p 80 testproject.asgi_for_ipc:channel_layer
   directory = /srv/channels/testproject/
   user = root
-  
+
   [program:worker]
   command = python manage.py runworker --settings=testproject.settings.channels_ipc
   directory = /srv/channels/testproject/
   user = root
-  
-  
+
+
   [group:django_channels]
   programs=daphne,worker
   priority=999