Zulip supports a feature called “typing indicators.”
Typing indicators are status messages that tell you when another user is composing a message to you. Zulip’s typing UI is similar to what you see in other chat/text systems.
This document describes how we have implemented the feature in Zulip, and our main audience is developers who want to understand the system and possibly improve it. This document assumes that the client is our web app, but any client can play along with this protocol.
Right now typing indicators are only used in “Private messages” views.
There are two major roles for users in this system:
The “writing user” is composing a message.
The “receiving user” is waiting to receive a message (or possibly ready to shift their attention elsewhere).
Any Zulip user can play either one of these roles, and sometimes they can be playing both roles at once. Having said that, you can generally understand the system in terms of a single message being composed by the “writing user.”
On a high level the typing indicators system works like this:
The client for the “writing user” sends requests to the server.
The server broadcasts events to other users.
The clients for “receiving users” receive events and conditionally show typing indicators, depending on where the clients are narrowed.
When a “writing user” starts to compose a message, the client app
sends a request to an endpoint called
/json/typing with an
start and a list of potential message recipients. The JS
function that facilitates this is called
If the “writing user” is composing a long message, we want to send repeated updates to the server, so that downstream clients know that the user is still typing. (Zulip messages tend to be longer than messages in other chat/text clients, so this detail is important.)
We have a small state machine in
makes sure subsequent “start” requests get sent out every ten
seconds. (This document is intended to describe the high level
architecture; the actual time values may be tuned in future releases.
See the constant
TYPING_STARTED_WAIT_PERIOD, for example.)
If the “writing user” goes more than five seconds without any text
input, then we send a request with an
stop. We also send
“stop” messages when the user explicitly aborts composing a message
by closing the compose box (or other actions).
A common scenario is that a user is just pausing to think for a few seconds, but they still intend to finish the message. Of course, that’s hard to distinguish from the scenario of the user got pulled away from their desk. For the former case, where the “writing user” completes the message with lots of pauses for thinking, a series of “start” and “stop” messages may be sent over time. Timeout values reflect tradeoffs, where we have to guess how quickly people type, how long they pause to think, and how frequently they get interrupted.
The server piece of typing notifications is currently pretty straightforward, since we take advantage of Zulip’s events system.
We deliberately designed the server piece to be stateless, which minimizes the possibility of backend bugs and gives clients more control over the user experience.
As such, the server piece here is basically a single Django view function with a small bit of library support to send out events to clients.
Requests come into
/json/typing. The view mostly calls out
check_send_typing_notification to do the heavy lifting.
One of the main things that the server does is to simply validate
to users are for valid, active users in the realm.
Once the request has been validated, the server sends events to
potential recipients of the message. The event type for that
typing. See the function
for more details.
When a user plays the role of a “receiving user,” the client handles incoming “typing” events from the server, and the client will display typing notification only when both of these conditions are true:
The “writing user” is still likely typing.
The “receiving user” is in a view where they’d see the eventual message.
The client code starts by processing events, and it maintains data structures, and then it eventually shows or hides status messages.
We’ll describe the flow of data through the web app as a concrete example.
The events will come in to
start operations get further handled by
The main goal is then to triage which events should lead to display changes.
The web app client maintains a list of incoming “typists” using
static/js/typing_data.js. The API here has functions
like the following:
One subtle thing that the client has to do here is to maintain
timers for typing notifications. The constant
TYPING_STARTED_EXPIRY_PERIOD is used to determine that the
“writing user” has abandoned the message. Of course, the
“writing user” will also explicitly send us
at certain times.
When it finally comes to displaying the notification, the web
app eventually calls
Even though the server is stateless, any developer working on a client needs to be mindful of timing/network considerations that affect the overall system.
In general, client developers should agree on timeout parameters for how frequently we “kickstart” typing notifications for users sending long messages. This means standardizing the “writing user” piece of the system. It’s possible that certain clients will have slightly different mechanisms for detecting that users have abandoned messages, but the re-transmit frequency should be similar.
When implementing the “receiving user” piece, it’s important to realize how clients behave on the other end of the protocol. It’s possible, for example, to never receive a “stop” notification from a client that was shut down abruptly. You should allow reasonable amounts of time for the other side to send notifications, allowing for network delays and server delays, but you should not let the notifications become too “sticky” either.
This document is being written just under a year after typing indicators were first implemented. The feature has been popular, and after some initial cleanup, it has not required a lot of maintenance.
The most likely big change to typing indicators is that we will add them for stream conversations. This will require some thought for large streams, in terms of both usability and performance.
Another area for refinement is to tune the timing values a bit.
Right now we are probably too aggressive about sending
messages, when users often are just pausing. It’s possible
to better account for typing speed or other heuristic things
like how much of the message has already been typed.
From an infrastructure perspective, we should be mindful of bandwidth concerns. A fairly easy change would be to send user ids instead of emails.
Some folks may want to turn off typing indicators, so we will eventually want customized settings here.