Previously, entering a non-UTC end time for a daily stat would give you
incorrect results. This is because:
* All daily stats are collected at and have end_times in the database in
midnight UTC.
* For daily stats, time_range returns a list of datetimes at midnight in the
timezone of its end argument. These datetimes are the only ones we look
for when looking for rows corresponding to the stat in the database.
* Previously, we passed on the end argument from the API to time_range,
without modification.
This consists of the `zulip_ops::stats` Puppet class, which has apparently
not been used since 2014, and a number of files that I believe were
only used for that. Also a couple of tiny loose ends in other files.
sort_client_labels sorts first by total, and then to ensure deterministic
outcomes, sorts (reverse) alphabetically by label.
Fixes regression introduced in 0c0e539.
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.
Rename 'zulip_internal' decorator to 'require_server_admin', add
documentation for 'server_admin', explaining how to give permission
for ./activity page.
Fixes: #1463.
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.
It will simplify the logic needed to process the "Sent by Me" view in
Messages Sent Over Time in stats.js.
Also, we gzip the data sent from our server, so there is little additional
network usage by doing this.
Django 1.10 has changed the implementation of this function to
match our custom implementation; in addition to this, we prefer
render().
Fixes#1914 via #4093.
API: Adds a "display_order" to the response, which is a suggested order of
importance for the clients or recipient types respectively.
frontend: Changes messages_sent_by_{client,recipient_type} to use a fixed
order for any given user.
Also includes a number of changes to messages_sent_by_recipient_type that
were convenient to do at the same time, since the two charts share a lot of
code.
This adds a frontend for the analytics system we've had for a few
months, showing several graphs of the data in Zulip.
There's a ton more that we can do with this tooling, but this initial
version is enough to provide users with a pretty good experience.
Fixes#2052.
Makes a number of simplications to the analytics views code. The main one is
that we now return the entire data series, even if the data is eventually
going to go into a pie chart. This was prompted by us wanting several
different pie charts for each stat (one for last 30 days, one for all time,
etc), but I think it is also a more natural API. The total amount of data
being sent for the pie charts now is maybe half of what is being sent for
our single 'hourly' stat, or maybe up to 10,000 ints per year the
organization has been around.
The other big change is that the data being sent back is now always explicit
about whether it is data about the realm (stored in data['realm'], or data
about the user (stored in data['user']).
Not sure if this would actually be a performance problem in practice, but
this was originally making a database query for each subgroup (instead of
just a single query getting data for all the subgroups).
Also removed the filter against the interval column, which will soon not be
needed (interval will be uniquely determined by the property).
Tim Abbott
rht
Rishi Gupta
Greg Price
Aditya Bansal
umkay
Maxim Averin
hackerkid
hollywoodno
Umair Khan
Raghav Jajodia
Amy Liu