We only use this in the direct management command, and it involves
some autoreload process setup stuff that we probably don't want to do
in our unit tests regardless.
This is basically a simple fix, where we consistently set
`flags` to an empty array when we pass it around. The history
here is that we had kind of a nasty bug from setting it to
`None`, which only showed up in the somewhat obscure circumstance
of somebody subscribing to all stream events in our API.
Fixes#7921
A `None` value is not properly handled in this function, which
indicates some lack of testing or a recent regression we don't
understand. We were getting lots of tracebacks from this line
of code on our test server:
mentioned = 'mentioned' in flags and 'read' not in flags
This method was new in Tornado 4.0. It saves us from having to get
the time ourselves and do the arithmetic -- which not only makes the
code a bit shorter, but also easier to get right. Tornado docs (see
http://www.tornadoweb.org/en/stable/ioloop.html) say we should have
been getting the time from `ioloop.time()` rather than hardcoding
`time.time()`, because the loop could e.g. be running on the
`time.monotonic()` clock.
This commit allows clients to register client_gravatar=True, and
then we recognize that flag for message events. If the flag is
True, we will not calculate gravatar URLs and let the clients do
it themselves. (Clients can calculate gravatar URLs based on
emails with just a little bit of code.)
This refactoring doesn't change behavior, but it sets us up
to more easily handle a register setting for `client_gravatar`,
which will allow clients to tell us they're going to compute
their own gravatar URLs.
The `client_gravatar` flag already exists in our code, but it
is only used for Django views (users/messages) but not for
Zulip events.
The main change is to move the call to `set_sender_avatar` into
`finalize_payload`, which adds the boolean `client_gravatar`
parameter to that function. And then we update various callers
to supply that flag.
One small performance benefit of this change is that we now
lazily compute the client message payloads in
`event_queue.process_message_event` now, so this will improve
performance if all interested clients have the same value of
`apply_markdown`. But the change here is really preparing us
for the additional boolean parameter, which will cause us to
have four variations of the payload.
This test helper method duplicated a bunch of logic in
`zerver/worker/queue_processors.py` in a specialized fashion for the
tests. Now that we're using `call_consume_in_tests` in this code
path, we don't need it.
In do_send_messages, we only produce one dictionary for
the event queues, instead of different flavors for text
vs. html. This prevents two unnecessary queries to the
database.
It also means we only put one dictionary on the "message"
event queue instead of two, albeit a wider one that has
some values that won't be sent to the actual clients.
This wider dictionary from MessageDict.wide_dict is also
used for the `feedback_messages` queue and service bot
queues. Since the extra fields are possibly useful down
the road, and they'll just be ignored for now, we don't
bother to remove them. Also, those queue processors won't
have access to `content_type`, which they shouldn't need.
Fixes#6947
This removes the utterly unnecessary `triggers` dict (which always was
a dict with exactly one value True) in favor of a single field,
'trigger'.
Inspired by Kunal Gupta's work in #6659.
While the missedmessage_hook logic originally did a reasonably good
job of avoiding double-sending notifications, there was a corner case
it didn't handle, namely a user who had been presence-idle when a
message was sent and became also event-queue-idle as well within the
next 10 minutes. For those users, they got a notification at message
send time, and the missedmessage_hook would deliver it a second time.
We fix this by just checking the conveniently available push_notified
and email_notified variables that indicate whether the message already
had a notification triggered.
Fixes#7031.
This makes tests of queue processors more realistic,
by adding a parameter to `queue_json_publish` that
calls a queue's consumer function if accessed in a test.
Fixes part of #6542.
This field would get overwritten with an improper value when
we looped over multiple clients, due to not making full copies
of the message dictionary. This failure would be somewhat
random depending on how clients were ordered in the loop.
The only consumers of this field were the mobile app and the
apply-events-to-unread-counts logic. Both of these will now
use `flags` instead.
We now do push notifications and missed message emails
for offline users who are subscribed to the stream for
a message that has been edited, but we short circuit
the offline-notification logic for any user who presumably
would have already received a notification on the original
message.
This effectively boils down to sending notifications to newly
mentioned users. The motivating use case here is that you
forget to mention somebody in a message, and then you edit
the message to mention the person. If they are offline, they
will now get pushed notifications and missed message emails,
with some minor caveats.
We try to mostly use the same techniques here as the
send-message code path, and we share common code with the
send-message path once we get to the Tornado layer and call
maybe_enqueue_notifications.
The major places where we differ are in a function called
maybe_enqueue_notifications_for_message_update, and the top
of that function short circuits a bunch of cases where we
can mostly assume that the original message had an offline
notification.
We can expect a couple changes in the future:
* Requirements may change here, and it might make sense
to send offline notifications on the update side even
in circumstances where the original message had a
notification.
* We may track more notifications in a DB model, which
may simplify our short-circuit logic.
In the view/action layer, we already had two separate codepaths
for send-message and update-message, but this mostly echoes
what the send-message path does in terms of collecting data
about recipients.
Aditya Bansal
Tim Abbott
Steve Howell
neiljp (Neil Pilgrim)
rht
fredfishgames
Arseny Chekanov
Greg Price
Robert Hönig