This commit puts the guts of parse_usermessage_flags into
UserMessage.flags_list_for_flags, since it was slightly faster
than the old implementation and produced the same results.
(Both algorithms were super fast, actually.)
And then all callers use the model method now.
The logic to set search_fields was essentially the same for both
sides of the include_history conditional.
Now we have just one code block that sets search_fields, and we
can quickly short-circuit the loop when is_search is False.
tsearch_extras returns search offsets in bytes but our highlight
function treated them as character offsets. Added a check to subtract
extra bytes if the tsearch search backend is being used.
Fixes#4084.
Fixes#7021.
Do you call get_recipient(Recipient.STREAM, stream_id) or
get_recipient(stream_id, Recipient.STREAM)? I could never
remember, and it was not very type safe, since both parameters
are integers.
Before this change, we populated two cache entries for each
message that we sent. The entries were largely redundant,
with the only difference being whether we sent the content
as raw markdown or as the rendered HTML.
This commit makes it so we only have one cache entry per
message, and it includes both content and rendered_content.
One legacy source on confusion here is that `content`
changes meaning when you're on the front end. Here is the
situation going forward:
database:
content = raw
rendered_contented = rendered
cache entry:
content = raw
rendered_contented = rendered
payload for the frontend:
content = raw (for apply_markdown=False)
content = rendered (for apply_markdown=True)
Clients fetching messages can now specify that they are able
to compute their avatar, and if they set client_gratavar to
True in the request (w/our normal encoding scheme), then the
backend will not compute it, and the payload will be smaller.
The fix starts with get_messages_backend. The flag gets
passed down through these functions:
* MessageDict.post_process_dicts.
* MessageDict.set_sender_avatar.
We also fix up the callers for post_process_dicts to explicitly
pass in the client_gravatar path, but for now they all just hard
code the value to False.
Message.get_raw_db_rows is moved to MessageDict, since its
implementation details are highly coupled to other methods
in MessageDict.
And then sew_messages_and_reactions comes along for the
ride.
We eventually want to move Reaction.get_raw_db_rows to there
as well.
Introduce MessageDict.post_process_dicts() will allow us
the ability to do the following:
* use less memory in the cache for repeated data
* prevent cache invalidation
* format data according to different client needs
The first use of this function is pretty inconsequential, but
it sets us up for more consequential changes.
In this commit we defer the MessageDict.hydrate_recipient_info
step until after we pull data out of the cache. This impacts
cache size as follows:
* streams - negligibly bigger
* PMs/huddles - slimmer due to not needing to repeat
sender data like email/full_name
Again, the main point of this change is to start setting up
the infrastructure to do post-processing.
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.
We want to convert stream names to stream ids as close
to the "edges" of our system as possible, so we let our
caller do the work of finding the stream id for a stream
narrow.
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 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.
For filters like has:link, where the web app doesn't necessarily
want to guess whether incoming messages meet the criteria of the
filter, the server is asked to query rows that match the query.
Usually these queries are search queries, which have fields for
content_matches and subject_matches. Our logic was handling those
correctly.
Non-search queries were throwing an exception related to tuple
unpacking. Now we recognize when those fields are absent and
do the proper thing.
There are probably situations where the web app should stop hitting
this endpoint and just use its own filters. We are making the most
defensive fix first.
Fixes#6118
Before this change, server searches for both
`is:mentioned` and `is:alerted` would return all messages
where the user is specifically mentioned (but not
at-all mentions).
Now we follow the JS semantics:
is:mentioned -- all mentions, including wildcards
is:alerted -- has an alert word
Here is one relevant JS snippet:
} else if (operand === 'mentioned') {
return message.mentioned;
} else if (operand === 'alerted') {
return message.alerted;
And here you see that `mentioned` is OR'ed over both mention flags:
message.mentioned = convert_flag('mentioned') || convert_flag('wildcard_mentioned');
The `alerted` flag on the JS side is a simple mapping:
message.alerted = convert_flag('has_alert_word');
Fixes#5020
The new endpoints are:
/json/mark_stream_as_read: takes stream name
/json/mark_topic_as_read: takes stream name, topic name
The /json/flags endpoint no longer allows streams or topics
to be passed in as parameters.
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 mostly a pure code extraction, except that we now
disregard the `messages` option for stream/topic updates,
since the web app always passes in an empty list (and this
commit is really just an incremental step toward creating
new endpoints.)
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.
Rhea Parekh
picapi_
rht
Robert Hönig
Sampriti Panda
Steve Howell
YJDave
neiljp (Neil Pilgrim)
Greg Price
Tim Abbott