This fixes a batch of mypy errors of the following format:
'Item "None" of "Optional[Something]" has no attribute "abc"
Since we have already been recklessly using these attritbutes
in the tests, adding assertions beforehand is justified presuming
that they oughtn't to be None.
This function had a confusing name, which could result in someone
using it unintentionally when they meant do_reactivate_user.
We also add docstrings for both functions.
This is a prep commit. Currenty we only pass CountStat.property
to last_successful_fill function. But it needs access to
CountStat.time_increment as well. We can pass the entire CountStat
object to the function as a workaround. But making last_successful_fill
a property of CountStat seems to be much more cleaner.
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.
Whenever we use API queries to mark messages as read we now increment
two new LoggingCount stats, messages_read::hour and
messages_read_interactions::hour.
We add an early return in do_increment_logging_stat function if there
are no changes (increment is 0), as an optimization to avoid
unnecessary database queries.
We also log messages_read_interactions::hour Logging stat
as the number of API queries to mark messages as read.
We don't include tests for the case where do_update_pointer is called
because do_update_pointer will most likely be removed from the
codebase in the near future.
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>
At the time of creating streams in test_counts.py we earlier did not saved
recipient in the stream object.
stream.recipient is used in many functions so they would throw error.
The right long-term fix here is probably to just use the standard
stream creation functions rather than having a hacky duplicate
here.
datetime.timezone is available in Python ≥ 3.2. This also lets us
remove a pytz dependency from the PostgreSQL scripts.
Signed-off-by: Anders Kaseorg <anders@zulip.com>
We change do_create_user and create_user to accept
role as a parameter instead of 'is_realm_admin' and 'is_guest'.
These changes are done to minimize data conversions between
role and boolean fields.
mock is just a backport of the standard library’s unittest.mock now.
The SAMLAuthBackendTest change is needed because
MagicMock.call_args.args wasn’t introduced until Python
3.8 (https://bugs.python.org/issue21269).
The PROVISION_VERSION bump is skipped because mock is still an
indirect dev requirement via moto.
Signed-off-by: Anders Kaseorg <anders@zulip.com>
Generated by autopep8, with the setup.cfg configuration from #14532.
I’m not sure why pycodestyle didn’t already flag these.
Signed-off-by: Anders Kaseorg <anders@zulipchat.com>
Replaced unique_together with UniqueConstraint in models that
covered nullable fields as in unique_together database indexes
don't work where subgroup=None. So added conditional unique
index handling invalid duplicate Count data.
Added 0015_clear_duplicate_counts migration to handle existing
data that violates the constraints.
Also corrected a test case in test_counts.py which didn't clear its
state properly and thus was accidentally taking advantage of this
database schema bug.
This changeset is prepartory work for doing something reasonable with
analytics data during the zulip -> zulip data import process (and
potentially e.g. slack -> Zulip as well).
To support that, we need to make it possible to do our analytics
calculations for a single realm.
We do this while maintaining backwards compatibility and avoiding
massive duplicated code by adding an optional `realm` argument to the
entrypoints to the analytics system, especially process_count_stat.
More work involving restructuring FillState will be required for this
to be actually usable for its intented purpose, but this commit is a
nice checkpoint along the way.
Tweaked by tabbott to adjust comments and disable InstallationCount
updates when a realm argument is specified.
MigrationsTestCase is intentionally omitted from this, since migrations
tests are different in their nature and so whatever setUp()
ZulipTestCase may do in the future, MigrationsTestCase may not
necessarily want to replicate.
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.
Previous cleanups (mostly the removals of Python __future__ imports)
were done in a way that introduced leading newlines. Delete leading
newlines from all files, except static/assets/zulip-emoji/NOTICE,
which is a verbatim copy of the Apache 2.0 license.
Signed-off-by: Anders Kaseorg <anders@zulipchat.com>
Previously we would update FillState for daily stats on hourly boundaries as
well. This would create two extra queries on the FillState table every hour
(for each CountStat), which adds roughly 50ms of extra processing for each
CountStat each day, as well as two extra lines each hour in the analytics
log. This can be a minor annoyance when backfilling stats.
I think this is more pythonic?
We could also get rid of LoggingCountStats altogether, since it's now just a
special case of CountStat (is_logging == data_collector.pull_function is None).
But I think it's nice to keep the distinction since they behave so differently.
This will allow us to appropriately generalize CountStat to include
LoggingCountStat and CustomPullCountStat. It'll also make life easier when
we introduce DependentCountStat.
It turned out to not be that useful once we added subgroup. The previous
design of the CountStat object also assumed more reuseability of the *_query
strings than what ended up happening.
The filter_args also had some carrying costs:
* It's hard to be confident that filter_args other than the ones explicitly
in our tests would have had expected behavior.
* The filter_args/join_args system is the most complex part of the CountStat
object, and makes understanding the *_query strings unnecessarily
difficult for a new contributor.
Groundwork for allowing stats like "Monthly Active Users".
CountStat.interval is no longer as clean a value as before, so removed it
from views.get_chart_data. It wasn't being used by the frontend anyway.
Removing interval from logger calls in counts.py is not a big loss since we
now include the frequency (which is typically also the interval) in
CountStat.property.
Analytics database tables are getting big, and so we're likely moving to a
model where ~all stats are day stats, and we keep hourly stats only for the
last N days.
Also changed the name because:
* messages_sent_* suggests the counts (summed over subgroup) should be the
same as the other messages_sent stats, but they are different (these don't
include PMs).
* messages_sent_by_stream:is_bot:day is longer than 32 characters, the max
allowable length for a BaseCount.property.
Includes a database migration to remove the old stat from the analytics
tables.
Having both messages_sent:hour and messages_sent:is_bot:day is confusing,
since a single messages_sent:is_bot:hour would have a superset of the
information and take less total space. This commit and its parent together
replace the two stats with a single messages_sent:is_bot:hour.
Includes a database migration. The interval field was originally there to
facilitate time aggregation (e.g. aggregate_hour_to_day), but we now do such
aggregations in views code or in the frontend.
A few reasons:
* Our two other subgroup'd message stats in UserCount are at CountStat.DAY
frequency (messages_sent:is_bot and messages_sent:message_type).
* Keeping this stat at hourly frequency would likely double the size of our
analytics table, given the current stats. (Counterpoint: if there are
roughly as many active streams as active users, and we keep
messages_sent_to_stream:is_bot at hourly frequency, then maybe this stat
is only a 30% or 50% increase).
* We're currently only showing this on the frontend as a pie chart anyway.
PIG208
akshatdalton
Tim Abbott
Vishnu KS
shanukun
Mateusz Mandera
Anders Kaseorg
Steve Howell
arpit551
Sahil Batra
Anders Kaseorg
Mateusz Mandera
Rishi Gupta
Tim Abbott
Anders Kaseorg
Steve Howell
Nikhil Kumar Mishra
Aditya Bansal
rht
neiljp (Neil Pilgrim)
Vishnu Ks
umkay
hollywoodno
Raghav Jajodia
aakash-cr7