This deletes the unused Subscription.notifications field and removes
it from some testing and analytics code (which should not have been
using it in the first place).
Fixes#10042.
This fixes a subtle bug where if you reran populate_analytics_db
directly, we'd end up in a weird state where memcached fetched the
"old" pre-flush UserProfile object for shylock when loading /stats,
which ultimately would result in /stats appearing totally broken.
These are no longer useful, with our spiffy new analytics framework,
and we haven't in fact been using them for some time, while the
`active-user-stats` cron job does cause regular mail from cron.
Just delete them.
Previously we showed the total number of users with an active account. This
changes it to show only the number of users that have logged in in the past
two weeks.
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.
Originally, all the client names in populate_analytics_db started with
underscores to make it easy to selectively delete and regenerate them when
re-running populate_analytics_db.
We eventually want to merge populate_analytics_db into populate_db though,
in which case it makes more sense for them to share client names, and not
worry about the case where we run (or re-run) populate_analytics_db
independently of populate_db.
When you pass a naive datetime to the Django ORM, it uses settings.TIME_ZONE
for the time zone. In the development environment, both settings.TIME_ZONE
and datetime.now() use 'America/New_York', so there is no change in behavior
there. (fromtimestamp with no tz argument uses the same timezone as
datetime.now)
We are soon going to change settings.TIME_ZONE to UTC, so need to remove
naive datetimes from queries to the ORM.
This actually fixes previously broken behavior, since 'date' here gets
turned into the 'day' argument of seconds_active_during_day(day), where
tzinfo is set to UTC.
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.
Previously, this function seemed ambivalent about whether it was generating
a series of abstract data points or a series of data points that would
correspond to times. Switch firmly to the latter, so e.g. if the frequency
changes, so will the length of the output sequence.
We were updating FillState with FillState.objects.filter(..).update(..),
which does not update the last_modified field (which has auto_now=True).
The correct incantation is the save() method of the actual FillState
object.
Finishes the refactoring started in c1bbd8d. The goal of the refactoring is
to change the argument to get_realm from a Realm.domain to a
Realm.string_id. The steps were
* Add a new function, get_realm_by_string_id.
* Change all calls to get_realm to use get_realm_by_string_id instead.
* Remove get_realm.
* (This commit) Rename get_realm_by_string_id to get_realm.
Part of a larger migration to remove the Realm.domain field entirely.
Adds two simplifying assumptions to how we process analytics stats:
* Sets the atomic unit of work to: a stat processed at an hour boundary.
* For any given stat, only allows these atomic units of work to be processed
in chronological order.
Adds a table FillState that, for each stat, keeps track of the last unit of
work that was processed.
This is a first pass at building a framework for collecting various
stats about realms, users, streams, etc. Includes:
* New analytics tables for storing counts data
* Raw SQL queries for pulling data from zerver/models.py tables
* Aggregation functions for aggregating hourly stats into daily stats, and
aggregating user/stream level stats into realm level stats
* A management command for pulling the data
Note that counts.py was added to the linter exclude list due to errors
around %%s.
ss62171
Tim Abbott
Roman Godov
Anders Kaseorg
Vishnu Ks
Eeshan Garg
Nikhil Kumar Mishra
Rishi Gupta
Aditya Bansal
neiljp (Neil Pilgrim)
Archana BS
rht
derAnfaenger
Greg Price
Vishnu Ks
umkay
hollywoodno
Raghav Jajodia
umkay
reyha
Sidhant Bhavnani
Rafid Aslam
Umair Khan
Taranjeet
Tim Abbott
Eklavya Sharma
Ashish
Steven Oud