Added emojis and Non ASCII characters to default
stream names and descriptions.
Added raw_emojis array under streams so that
we can pass --extra-streams argument without
--extra-users as it should be.
Added non ascii and non bmp characters to stream names.
A Stream Name will now consist of a random stream name +
a number (to avoid name duplicates) + a 15% to contain
a emoji.
Added non ASCII and non bmp characters to full name.
Created a new list for non_ascii_names and emojis
to store them explicitly.
A full name will now consist of first name +
(a non ASCII name or a plain middle name) + (a emoji
or a plain last name).
First name will not have any non ASCII or non bmp text
as it is also being used as email.
This adds the is_user_active with the appropriate code for setting the
value correctly in the future. In the following commit a migration to
backfill the value for existing Subscriptions will be added.
To ensure correct user_profile.is_active handling also in tests, we
replace all direct .is_active mutation with calls to appropriate
functions.
Note that at this point, it's not possible to create moderator users;
this just will make it easier to write tests for logic involving them
as we develop the feature.
user_profile.id was confused for user_profile.recipient_id. These bugs
are particularly sneaky as they can go undetected by tests due to ids of
objects accidentally coinciding. We add a mitigation for this class of
mistakes by shifting the Recipient.id sequence in test db.
This was introduced in dda3ff41e1.
On the rare occasion where user_profile.id would coincide with
recipient_id passed to the function, we would return the wrong value.
That is, instead of correctly returning recipient_id, we would return
sender.recipient_id - recipient id of the sender of the message, thus
possibly returning user_profile.recipient_id (if user_profile is the
sender) - exactly the situation the function wanted to avoid
with the `if recipient_id == my_recipient_id:` if. Ultimately resulting
in incorrect/malformed data in
state['raw_recent_private_conversations'].
For 3000 messages and 400 users, this saved
about 30 seconds.
We only do two queries per batch of messages
now, and the algorithm is easier to analyze,
as it's just three nested loops.
I think it's important that the callers understand
that bulk_add_subscriptions assumes all streams
are being created within a single realm, so I make
it an explicit parameter.
This may be overkill--I would also be happy if we
just included the assertions from this commit.
SIGALRM is the simplest way to set a specific maximum duration that
queue workers can take to handle a specific message. This only works
in non-threaded environments, however, as signal handlers are
per-process, not per-thread.
The MAX_CONSUME_SECONDS is set quite high, at 10s -- the longest
average worker consume time is embed_links, which hovers near 1s.
Since just knowing the recent mean does not give much information[1],
it is difficult to know how much variance is expected. As such, we
set the threshold to be such that only events which are significant
outliers will be timed out. This can be tuned downwards as more
statistics are gathered on the runtime of the workers.
The exception to this is DeferredWorker, which deals with quite-long
requests, and thus has no enforceable SLO.
[1] https://www.autodesk.com/research/publications/same-stats-different-graphs
We set wildcard_mention_policy in the test database so that we can
avoid future changes in mention puppeteer tests, as the default
membership of streams in the Zulip development organization is large
enough to prevent random users from using wildcard mentions.
We call build_message_send_dict from check_message instead of
do_send_messages.
This is a prep commit for adding a new setting for handling
wildcard mentions in large streams.
Having both of these is confusing; TORNADO_SERVER is used only when
there is one TORNADO_PORT. Its primary use is actually to be _unset_,
and signal that in-process handling is to be done.
Rename to USING_TORNADO, to parallel the existing USING_RABBITMQ, and
switch the places that used it for its contents to using
TORNADO_PORTS.
A few major themes here:
- We remove short_name from UserProfile
and add the appropriate migration.
- We remove short_name from various
cache-related lists of fields.
- We allow import tools to continue to
write short_name to their export files,
and then we simply ignore the field
at import time.
- We change functions like do_create_user,
create_user_profile, etc.
- We keep short_name in the /json/bots
API. (It actually gets turned into
an email.)
- We don't modify our LDAP code much
here.
The prior version clobbered all flags, which means
we had unrealistic values for is_private.
Now we only touch the unread flag, which
also means when we go next to create alert words,
those will now work.
Added new Event Type in AbstractRealmAuditLog STREAM_CREATED.
Since we finally create streams in create_stream_if_needed function
in zerver/lib/streams.py so logged realm_audit there.
Passed acting_user when create_stream_if_needed or ensure_stream
function is called.
Added tests in test_audit_log.
Fixes#2665.
Regenerated by tabbott with `lint --fix` after a rebase and change in
parameters.
Note from tabbott: In a few cases, this converts technical debt in the
form of unsorted imports into different technical debt in the form of
our largest files having very long, ugly import sequences at the
start. I expect this change will increase pressure for us to split
those files, which isn't a bad thing.
Signed-off-by: Anders Kaseorg <anders@zulip.com>
Automatically generated by the following script, based on the output
of lint with flake8-comma:
import re
import sys
last_filename = None
last_row = None
lines = []
for msg in sys.stdin:
m = re.match(
r"\x1b\[35mflake8 \|\x1b\[0m \x1b\[1;31m(.+):(\d+):(\d+): (\w+)", msg
)
if m:
filename, row_str, col_str, err = m.groups()
row, col = int(row_str), int(col_str)
if filename == last_filename:
assert last_row != row
else:
if last_filename is not None:
with open(last_filename, "w") as f:
f.writelines(lines)
with open(filename) as f:
lines = f.readlines()
last_filename = filename
last_row = row
line = lines[row - 1]
if err in ["C812", "C815"]:
lines[row - 1] = line[: col - 1] + "," + line[col - 1 :]
elif err in ["C819"]:
assert line[col - 2] == ","
lines[row - 1] = line[: col - 2] + line[col - 1 :].lstrip(" ")
if last_filename is not None:
with open(last_filename, "w") as f:
f.writelines(lines)
Signed-off-by: Anders Kaseorg <anders@zulipchat.com>
Arun Sankar
shanukun
Mateusz Mandera
tushar912
sahil839
Anders Kaseorg
Tim Abbott
Steve Howell
Alex Vandiver
Wes Galbraith
Hashir Sarwar
arpit551
Aman Agrawal
Anders Kaseorg