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.
get_realm is better in two key ways:
* It uses memcached to fetch the data from the cache and thus is faster.
* It does a case-insensitive query and thus is more safe.
This contains the various fixes that needed to be made in order to get
accurate statistics.
Most notably, the active_users_between function in the previous
version of zerver/lib/statistics.py was broken for end dates in the
past, because it used the UserActivity table to get its data -- so in
fact it really was querying "users last active between".
This commit isn't super clean, but I figure we're probably better off
having our latest code for historical usage data in git so it doesn't
bitrot and anyone can improve on it.
(imported from commit 24ff2f24a22e5bdc004ea8043d8da12deb97ff2f)
Move commands related to stats collection and reporting from
zilencer to analytics. To do this, we had to make "analytics"
officially an app.
(imported from commit 63ef6c68d1b1ebb5043ee4aca999aa209e7f494d)
Rishi Gupta
hackerkid
hollywoodno
Raghav Jajodia
Tim Abbott
umkay
reyha
Sidhant Bhavnani
Rafid Aslam
Anders Kaseorg
Umair Khan
Taranjeet
Tim Abbott
Eklavya Sharma
Ashish
Steven Oud
Reid Barton
Tim Abbott
Leo Franchi
Kevin Mehall
Steve Howell