mirror of https://github.com/zulip/zulip.git
266 lines
13 KiB
Markdown
266 lines
13 KiB
Markdown
# Real-time push and events
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Zulip's "events system" is the server-to-client push system that
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powers our real-time sync. This document explains how it works; to
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read an example of how a complete feature using this system works,
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check out the
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[new application feature tutorial](../tutorials/new-feature-tutorial.md).
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Any single-page web application like Zulip needs a story for how
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changes made by one client are synced to other clients, though having
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a good architecture for this is particularly important for a chat tool
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like Zulip, since the state is constantly changing. When we talk
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about clients, think a browser tab, mobile app, or API bot that needs
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to receive updates to the Zulip data. The simplest example is a new
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message being sent by one client; other clients must be notified in
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order to display the message. But a complete application like Zulip
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has dozens of different types of data that need to be synced to other
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clients, whether it be new streams, changes in a user's name or
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avatar, settings changes, etc. In Zulip, we call these updates that
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need to be sent to other clients **events**.
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An important thing to understand when designing such a system is that
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events need to be synced to every client that has a copy of the old
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data if one wants to avoid clients displaying inaccurate data to
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users. So if a user has two browser windows open and sends a message,
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every client controlled by that user as well as any recipients of the
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message, including both of those two browser windows, will receive
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that event. (Technically, we don't need to send events to the client
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that triggered the change, but this approach saves a bunch of
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unnecessary duplicate UI update code, since the client making the
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change can just use the same code as every other client, maybe plus a
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little notification that the operation succeeded).
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Architecturally, there are a few things needed to make a successful
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real-time sync system work:
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* **Generation**. Generating events when changes happen to data, and
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determining which users should receive each event.
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* **Delivery**. Efficiently delivering those events to interested
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clients, ideally in an exactly-once fashion.
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* **UI updates**. Updating the UI in the client once it has received
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events from the server.
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Reactive JavaScript libraries like React and Vue can help simplify the
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last piece, but there aren't good standard systems for doing
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generation and delivery, so we have to build them ourselves.
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This document discusses how Zulip solves the generation and delivery
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problems in a scalable, correct, and predictable way.
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## Generation system
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Zulip's generation system is built around a Python function,
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`send_event(realm, event, users)`. It accepts the realm (used for
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sharding), the event data structure (just a Python dictionary with
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some keys and value; `type` is always one of the keys but the rest
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depends on the specific event) and a list of user IDs for the users
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whose clients should receive the event. In special cases such as
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message delivery, the list of users will instead be a list of dicts
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mapping user IDs to user-specific data like whether that user was
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mentioned in that message. The data passed to `send_event` are simply
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marshalled as JSON and placed in the `notify_tornado` RabbitMQ queue
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to be consumed by the delivery system.
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Usually, this list of users is one of 3 things:
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* A single user (e.g. for user-level settings changes).
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* Everyone in the realm (e.g. for organization-level settings changes,
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like new realm emoji).
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* Everyone who would receive a given message (for messages, emoji
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reactions, message editing, etc.); i.e. the subscribers to a stream
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or the people on a private message thread.
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It is the responsibility of the caller of `send_event` to choose the
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list of user IDs correctly. There can be security problems if e.g. an
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event containing private message content is sent to the entire
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organization. However, if an event isn't sent to enough clients,
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there will likely be user-visible real-time sync bugs.
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Most of the hard work in event generation is about defining consistent
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event dictionaries that are clear, readable, will be useful to the
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wide range of possible clients, and make it easy for developers.
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## Delivery system
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Zulip's event delivery (real-time push) system is based on Tornado,
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which is ideal for handling a large number of open requests. Details
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on Tornado are available in the
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[architecture overview](../overview/architecture-overview.md), but in short it
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is good at holding open a large number of connections for a long time.
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The complete system is about 2000 lines of code in `zerver/tornado/`,
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primarily `zerver/tornado/event_queue.py`.
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Zulip's event delivery system is based on "long-polling"; basically
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clients make `GET /json/events` calls to the server, and the server
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doesn't respond to the request until it has an event to deliver to the
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client. This approach is reasonably efficient and works everywhere
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(unlike websockets, which have a decreasing but nonzero level of
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client compatibility problems).
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For each connected client, the **Event Queue Server** maintains an
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**event queue**, which contains any events that are to be delivered to
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that client which have not yet been acknowledged by that client.
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Ignoring the subtle details around error handling, the protocol is
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pretty simple; when a client does a `GET /json/events` call, the
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server checks if there are any events in the queue. If there are, it
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returns the events immediately. If there aren't, it records that
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queue as having a waiting client (often called a `handler` in the
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code).
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When it pulls an event off the `notify_tornado` RabbitMQ queue, it
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simply delivers the event to each queue associated with one of the
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target users. If the queue has a waiting client, it breaks the
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long-poll connection by returning an HTTP response to the waiting
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client request. If there is no waiting client, it simply pushes the
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event onto the queue.
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When starting up, each client makes a `POST /json/register` to the
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server, which creates a new event queue for that client and returns the
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`queue_id` as well as an initial `last_event_id` to the client (it can
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also, optionally, fetch the initial data to save an RTT and avoid
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races; see the below section on initial data fetches for details on
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why this is useful). Once the event queue is registered, the client
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can just do an infinite loop calling `GET /json/events` with those
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parameters, updating `last_event_id` each time to acknowledge any
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events it has received (see `call_on_each_event` in the
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[Zulip Python API bindings][api-bindings-code] for a complete example
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implementation). When handling each `GET /json/events` request, the
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queue server can safely delete any events that have an event ID less
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than or equal to the client's `last_event_id` (event IDs are just a
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counter for the events a given queue has received.)
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If network failures were impossible, the `last_event_id` parameter in
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the protocol would not be required, but it is important for enabling
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exactly-once delivery in the presence of potential failures. (Without
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it, the queue server would have to delete events from the queue as
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soon as it attempted to send them to the client; if that specific HTTP
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response didn't reach the client due to a network TCP failure, then
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those events could be lost).
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[api-bindings-code]: https://github.com/zulip/python-zulip-api/blob/master/zulip/zulip/__init__.py
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The queue servers are a very high-traffic system, processing at a
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minimum one request for every message delivered to every Zulip client.
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Additionally, as a workaround for low-quality NAT servers that kill
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HTTP connections that are open without activity for more than 60s, the
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queue servers also send a heartbeat event to each queue at least once
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every 45s or so (if no other events have arrived in the meantime).
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To avoid a large memory and other resource leak, the queues are
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garbage collected after (by default) 10 minutes of inactivity from a
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client, under the theory that the client has likely gone off the
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Internet (or no longer exists) access; this happens constantly. If
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the client returns, it will receive a "queue not found" error when
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requesting events; it's handler for this case should just restart the
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client / reload the browser so that it refetches initial data the same
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way it would on startup. Since clients have to implement their
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startup process anyway, this approach adds minimal technical
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complexity to clients. A nice side effect is that if the Event Queue
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Server server (which stores queues in memory) were to crash and lose
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its data, clients would recover, just as if they had lost Internet
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access briefly (there is some DoS risk to manage, though).
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(The Event Queue Server is designed to save any event queues to disk
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and reload them when the server is restarted, and catches exceptions
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carefully, so such incidents are very rare, but it's nice to have a
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design that handles them without leaving broken out-of-date clients
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anyway).
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## The initial data fetch
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When a client starts up, it usually wants to get 2 things from the
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server:
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* The "current state" of various pieces of data, e.g. the current
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settings, set of users in the organization (for typeahead), stream,
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messages, etc. (aka the "initial state").
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* A subscription to receive updates to those data when they are
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changed by a client (aka an event queue).
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Ideally, one would get those two things atomically, i.e. if some other
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user changes their name, either the name change happens after the
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fetch (and thus the old name is in the initial state and there will be
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an event in the queue for the name change) or before (the new name is
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in the initial state, and there is no event for that name change in
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the queue).
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Achieving this atomicity goals means we save a huge amount of work
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that the N clients for Zulip don't need to worry about a wide range of
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potential rare and hard to reproduce race conditions; we just have to
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implement things correctly once in the Zulip server.
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This is quite challenging to do technically, because fetching the
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initial state for a complex web application like Zulip might involve
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dozens of queries to the database, caches, etc. over the course of
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100ms or more, and it is thus nearly impossible to do all of those
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things together atomically. So instead, we use a more complicated
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algorithm that can produce the atomic result from non-atomic
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subroutines. Here's how it works when you make a `register` API
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request; the logic is in `zerver/views/events_register.py` and
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`zerver/lib/events.py`. The request is directly handled by Django:
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* Django makes an HTTP request to Tornado, requesting that a new event
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queue be created, and records its queue ID.
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* Django does all the various database/cache/etc. queries to fetch the
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data, non-atomically, from the various data sources (see
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the `fetch_initial_state_data` function).
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* Django makes a second HTTP request to Tornado, requesting any events
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that had been added to the Tornado event queue since it
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was created.
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* Finally, Django "applies" the events (see the `apply_events`
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function) to the initial state that it fetched. E.g. for a name
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change event, it finds the user data in the `realm_user` data
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structure, and updates it to have the new name.
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### Testing
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The design above achieves everything we desire, at the cost that we
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need to write a correct `apply_events` function. This is a difficult
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function to implement correctly, because the situations that it tests
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for almost never happen (being race conditions). So we have a special
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helper test class, `BaseAction`, that is specifically designed to
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test this function by ensuring the possible race condition always
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happens. In particular, it does the following:
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* Call `fetch_initial_state_data` to get the current state.
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* Call a state change function that issues an event,
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e.g. `do_change_full_name`, and capture any events that are generated.
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* Call `apply_events(state, events)`, and compare the resulting
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"hybrid state" to what one would get from calling
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`fetch_initial_state_data` again now.
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The `apply_events` code is correct if those two results are identical.
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The `BaseAction` tests in `test_events` will print a diff
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between the "hybrid state" and the "normal state" obtained from
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calling `fetch_initial_state_data` after the changes. Those tests
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also inspect the events generated to ensure they have the expected
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format. Also, `verify_action` has the `state_change_expected` and `num_events`
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arguments that configure how many events that it asserts were
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generated and whether it expects the state after applying the events
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to differ what what it was before (which help catch common classes of
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bugs).
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The final detail we need to ensure that `apply_events` always works
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correctly is to make sure that we have relevant tests for
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every event type that can be generated by Zulip. This can be tested
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manually using `test-backend --coverage BaseAction` and then
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checking that all the calls to `send_event` are covered. Someday
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we'll add automation that verifies this directly by inspecting the
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coverage data.
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In the Zulip webapp, the data returned by the `register` API is
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available via the `page_params` parameter.
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### Messages
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One exception to the protocol described in the last section is the
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actual messages. Because Zulip clients usually fetch them in a
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separate AJAX call after the rest of the site is loaded, we don't need
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them to be included in the initial state data. To handle those
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correctly, clients are responsible for discarding events related to
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messages that the client has not yet fetched.
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Additionally, see
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[the master documentation on sending messages](../subsystems/sending-messages.md)
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