channels_rabbitmq

A Django Channels channel layer that uses RabbitMQ as its backing store.

Installation

pip install channels_rabbitmq

Usage

Then set up the channel layer in your Django settings file like so:

CHANNEL_LAYERS = {
    "default": {
        "BACKEND": "channels_rabbitmq.core.RabbitmqChannelLayer",
        "CONFIG": {
            "host": "amqp://guest:guest@127.0.0.1/asgi",
        },
    },
}

Possible options for CONFIG are listed below.

host

URL of the server to connect to, adhering to RabbitMQ spec. To connect to a RabbitMQ cluster, use a DNS server to resolve a hostname to multiple IP addresses. channels_rabbitmq will automatically reconnect if at least one of them is reachable in case of a disconnection.

expiry

Message expiry in seconds. Defaults to 60. You generally shouldn't need to change this, but you may want to turn it down if you have peaky traffic you wish to drop, or up if you have peaky traffic you want to backlog until you get to it.

group_expiry

Group expiry in seconds. Defaults to 86400. Channels will be removed from the group after this amount of time. It's recommended that you increase this parameter to 86400000 (1 year) and rely on explicit group_discard() to cancel subscriptions. (If your process halts, the group membership will disappear from RabbitMQ immediately: you needn't worry about leaks.)

local_capacity

Number of messages queued in memory. Defaults to 100. (A message sent to a group with two channels counts as two messages.) When local_capacity messages are queued, the message backlog will grow on RabbitMQ.

remote_capacity

Number of messages stored on RabbitMQ for each client. Defaults to 100. (A message sent to a group with three channels on two distinct clients counts as two messages.) When remote_capacity messages are queued in RabbitMQ, the channel will refuse new messages. Calls from any client to send() or group_send() to the at-capacity client will raise ChannelFull.

prefetch_count

Number of messages to read from RabbitMQ at a time. Defaults to 10. This makes local_capacity a bit of a "loose" setting: if messages are queued rapidly enough, the client may request prefetch_count messages even if it already has local_capacity - 1 messages in memory. Higher settings accelerate throughput a little bit; lower settings help adhere to local_capacity more rigorously.

Design decisions

To scale enormously, this layer only creates one RabbitMQ queue per instance. That means one web server gets one RabbitMQ queue, no matter how many websocket connections are open. For each message being sent, the client-side layer determines the RabbitMQ queue name and uses it as the routing key.

Groups are implemented using a single, global RabbitMQ direct exchange called "groups". To send a message to a group, the layer sends the message to the "groups" exchange with the group name as the routing key. The client binds and unbinds during group_add() and group_remove() to ensure messages for any of its groups will reach it.

RabbitMQ queues are exclusive: when a client disconnects (through close or crash), RabbitMQ will delete the queue and unbind the groups.

Django Channels' specification does not account for "connecting" and "disconnecting", so this layer is always connected. It will reconnect forever in the event loop's background, logging warnings each time the connect fails.

Once a connection has been created, it pollutes the event loop so that async_to_sync() will destroy the connection if it was created within async_to_sync(). Each connection starts a background async loop that pulls messages from RabbitMQ and routes them to receiver queues; each receive() queries receiver queues. Empty queues are deleted. TODO delete queues that only contain expired messages, so we don't leak when sending to dead channels.

Dependencies

You'll need Python 3.6+ (lower hasn't been tested) and a RabbitMQ server.

If you have Docker, here's how to start a development server:

docker run --rm -it -p 5672:5672 rabbitmq:3.7.8-alpine

Alternatively, you can run it with a management interface at http://localhost:15672:

docker run --rm -it -p 5672:5672 -p 15672:15672 rabbitmq:3.7.8-management-alpine

Contributing

To add features and fix bugs

1. docker run --rm -it -p 5672:5672 -p 15672:15672 rabbitmq:3.7.8-management-alpine
2. python ./setup.py pytest # to ensure tests pass.
3. Write new tests in tests/ and make sure they fail.
4. Write new code in channels_rabbitmq/ to make the tests pass.
5. Submit a pull request.

To deploy

Use semver.

1. Change __version__ in channels_rabbitmq/__init__.py.
2. Add to CHANGELOG.rst.
3. git commit channels_rabbitmq/__init__.py CHANGELOG.rst -m 'vX.X.X' but don't push.
4. git tag vX.X.X
5. git push --tags && git push

TravisCI will push to PyPi.