This starts to phase out the need for UserProfile objects in
do_send_messages(). UserProfile objects are expensive to create
for large streams with lots of users. The objects in the code
before this commit aren't even full UserProfile objects.
This change mostly sets up future performance improvements, but
we also get a minor speedup here when we run a test with 3000
stream subscribers.
There is no reason for either render_incoming_message() or
render_markdown() to require full UserProfile objects just to
triage alert words.
By only asking for user_ids, we save extra queries in two
callpaths and we make it easier to start using user_ids in
do_send_messages().
This function is essentially a copy of get_recipient_user_profiles,
which is about to go away. The new function enforces the contract of
typing indicators, which is that they don't apply to streams, which
allows us to use a relatively simple approach for getting user
profile objects.
We are diverging this code, because the send-message path needs
more optimizations.
This change introduces an extra hop to the database, but it is
generally faster due to nuances of the DB and the ORM. It
also sets us up to optimize get_recipient_user_profiles() by
avoiding creating ORM objects.
I measured the impact of this using a stream with 3000
subscribers, half of whom were idle, and it speeds things up
by 10%.
Usually a small minority of users are eligible to receive missed
message emails or mobile notifications.
We now filter users first before hitting UserPresence to find idle
users. We also simply check for the existence of recent activity
rather than borrowing the more complicated data structures that we
use for the buddy list.
This commit completely switches us over to using a
dedicated model called MutedTopic to track which topics
a user has muted.
This includes the necessary migrations to create the
table and populate it from legacy data in UserProfile.
A subsequent commit will actually remove the old field
in UserProfile.
Admins need to know about private streams to delete them, even
if they are not subscribed. We send the minimal info possible
to the client to allow them to have a UI for that.
This never made sense to be a flag on the UserMessage table, since
it's not per-user state. And in fact it doesn't need to be in a
database at all, since it's easily computed from content anyway.
Fixes#1099.
This is mostly pure code extraction.
It also removes some dead code in update_muted_topic, where
were updating muted_topics spuriously before calling
do_update_muted_topic.
Unlike creating a stream, there's really no reason one would want to
call the function to create a realm while uncertain whether that realm
already existed.
This change is mostly based on a similar commit from hackerkid
in a feature branch. It borrows both code and ideas. Some of
it's my own stuff, as I was working on a newer branch.
We now call get_user_including_cross_realm_email() inside of
user_profiles_from_unvalidated_emails(), instead of using
get_user_profile_by_email.
This requires a few of our callers to pass down sender into us.
One consequence of this change is that we change the symptoms
for trying to send to emails outside of your realm. In some
cases, we simply raise an error that an email is invalid to us
instead of getting into the deeper validate_recipient_user_profiles
check.
We are trying to convert emails to user_profiles earlier in
the codepath. This may cause subtle changes in which errors
appear, but it's probably generally good to report on bad
addressees sooner than later.
This class simplifies the calling sequence to methods like
check_message and _internal_prep_message, and it's also more
type safe.
Checking for message types is encapsulated with calls to is_stream()
and is_private(). There are also shortcut constructors when you
know that the type of the address (stream vs. private), which is often.
This function optimizes marking streams and topics as read,
by using UserMessage.where_unread(), which uses a partial
index on the "read" flag.
This also simplifies the code path for ordinary message
flag updates.
In order to keep 100% line coverage, I simplified the
logging in update_message_flags, so now all requests
will show the "actually" format.
This is an interim step toward creating dedicated endpoints
for marking streams/topics as reads, so we do error checking
with asserts for flag/operation, so we don't introduce a
temporary translation string.
This is the first part of a larger migration to convert Zulip's
reactions storage to something based on the codepoint, not the emoji
name that the user typed in, so that we don't need to worry about
changes in the names we're using breaking the emoji storage.
We apparently were not correctly clearing the user_profile's email
address from caches when changing email addresses, which meant that
trying to look up the old email in the user_profile caches would still
work.
Fixes#6035.
The "all" option for 'message/flags' was dangerous, as it could
apply to any of our flags. The only flag it made sense for, the
"read" flag, now has a dedicated endpoint.
This change simplifies how we mark all messages as read. It also
speeds up the backend by taking advantage of our partial index
for unread messages. We also use a new statsd indicator.
We are adding a new list of unread message ids grouped by
conversation to the queue registration result. This will allow
clients to show accurate unread badges without needing to load an
unbound number of historic messages.
Jason started this commit, and then Steve Howell finished it.
We only identify conversations using stream_id/user_id info;
we may need a subsequent version that includes things like
stream names and user emails/names for API clients that don't
have data structures to map ids -> attributes.
In anticipation of have all unread message ids available to the
web app in page_params (via a separate effort), we are simplifying
the /topics endpoint to no longer return unread counts.
Instead we have a list of tiny dictionaries with these fields:
name - name of the topic
max_id - max message id for the topic (aka most recent)
The items in the list are order by most-recent-topic-first.
