Use read-only types (List ↦ Sequence, Dict ↦ Mapping, Set ↦
AbstractSet) to guard against accidental mutation of the default
value.
Signed-off-by: Anders Kaseorg <anders@zulip.com>
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>
Fixes#1727.
With the server down, apply migrations 0245 and 0246. 0246 will remove
the pub_date column, so it's essential that the previous migrations
ran correctly to copy data before running this.
We do not anticipate our UI for showing stream descriptions looking
reasonable for multi-line descriptions, so we should just ban creating
them.
Given the frontend changes, multi-line descriptions are only likely to
show up from importing content from other tools, in which case
replacing newlines with spaces is cleaner than the alternative.
This commit does the following three things:
1. Update stream model to accomodate rendered description.
2. Render and save the stream rendered description on update.
3. Render and save stream descriptions on creation.
Further, the stream's rendered description is also sent whenever the
stream's description is being sent.
This is preparatory work for eliminating the use of the
non-authoritative marked.js markdown parser for stream descriptions.
Our HipChat conversion tool didn't properly handle basic avatar
images, resulting in only the medium-size avatar images being imported
properly. This fixes that bug by asking the import tool to do the
thumbnailing for the basic avatar image (from the .original file) as
well as the medium avatar image.
The previous implementation used run_parallel incorrectly, passing it
a set of very small jobs (each was to download a single file), which
meant that we'd end up forking once for every file to download.
This correct implementation sends each of N threads 1/N of the files
to download, which is more consistent with the goal of distributing
the download work between N threads.
We (lexically) remove "subject" from the conversion code. The
`build_message` helper calls `set_topic_name` under the hood,
so things still have "subject" in the JSON.
There was good code coverage on `build_message`.
This was a pretty nasty error, where we were accidentally accessing
the parent list in this inner loop function.
This appears to have been introduced as a refactoring bug in
7822ef38c2.
We now use subscriber_map for building UserMessage
rows in Slack/Gitter conversions.
This is mostly designed to simplify the code, rather
than having to scan the entire subscribers for each
message.
I am guessing this will improve performance for most
conversions. We sort small lists on every message,
in order to be deterministic, but the sorting cost
is probably more than offset by avoiding the O(N)
scans across all subscriptions. Also, it's probably
negligible in the grand scheme of things, compared
to JSON parsing, file I/O, etc.
This commits also fixes some typos with mentioned_users_id ->
mentioned_user_ids and cleans up a test a bit as well.
We now have all three third party
conversions (Gitter/Slack/Hipchat)
go through build_user_message().
Hipchat was already using this helper.
We also avoid callers having to pass in
an id to build_user_message().
Having two smaller functions should make it
easier to customize the behavior for each specific
use case. The only reason they were ever coupled
was to keep ids in sequence, but the recent NEXT_ID
changes make that a non-issue now.
We extract this function and put it in the shared
library `import_util.py`.
Also, we make it one time higher up in the call
stack, rather than re-building it for every batch
of messages. I doubt this was super expensive, but
there's no reason to repeatedly execute this.
We simplify the code for is_realm_admin
and set is_guest as well.
I verified that build_user() is not used
by Slack/Gitter, so the extra argument there
should be fine.
Fixes#10639
This is a very early version of a tool to convert Hipchat
tar files into data files that can be used by the Zulip
import process.
We include the most fundamental entities--users and
streams. Customers who don't care about past messages
or customizations could start an instance off of this
and start communicating.
Of course, there are a lot of things missing in the
initial version:
* messages!
* file assets -- avatars, emojis, attachments
* probably lots of other minor things
We currently ignore any incoming dates from Hipchat data
and just use the current time. This is consistent with
other imports.
We also don't have any docs yet, although the process
will be extremely similar to the "Slack" process:
https://zulipchat.com/help/import-from-slack
Also, there's a comment at the top of convert_hipchat_data.py
that describes how to test this in dev mode.
I tested this by following the steps in the comment above.
The users just "show up" in /devlogin, so that's nice, and
you can send messages to other users. To verify the stream
data you have to go into the gear menu and click on "All
Streams", then you can subscribe and send a message.
Production users will need to get new passwords and
re-subscribe to streams. We will probably auto-subscribe
all users to public streams.
Anders Kaseorg
Anders Kaseorg
Stefan Weil
Vishnu KS
Rishi Gupta
Mateusz Mandera
Tim Abbott
Anders Kaseorg
Hemanth V. Alluri
Steve Howell
Rhea Parekh