This includes:
* Merging the pull request and issue subject creation functions
* Factoring out pull request and issue content creation
(imported from commit 9cf90e999482a1998431e6483788522101607167)
get_subscribers_backend() now calls the new get_subscriber_emails()
function, which just queries the email field:
"zerver_userprofile"."email"
...instead of querying about 40 fields that it never uses.
I was able to verify the query slimming by watching my postgres server log.
Also, you can verify that the ORM does roughly 16x less work using values():
>>> def f(): return [sub.user_profile.email for sub in list(Subscription.objects.all().select_related())]
...
>>> def g(): return [row['user_profile__email'] for row in list(Subscription.objects.all().values('user_profile__email'))]
...
>>> def timeit(func): t = time.time(); func(); return time.time() - t
...
>>> timeit(f)
0.045198917388916016
>>> timeit(g)
0.002752065658569336
(imported from commit a69f690a96d076b323fdfc2f4821b0548bdfac7f)
* Remove the action from the topic and add the issue title
* Only show the issue body on open or reopen
(imported from commit f08eb40f36122d2498fe0c36a69df9e606296ff3)
These engagement data will be useful both for making pretty graphs of
how addicted our users are as well as for allowing us to check whether
a new deployment is actually using the product or not.
This measures "number of minutes during which each user had checked
the app within the previous 15 minutes". It should correctly not
count server-initiated reloads.
It's possible that we should use something less aggressive than
mousemove; I'm a little torn on that because you really can check the
app for new messages without doing anything active.
This is somewhat tested but there are a few outstanding issues:
* Mobile apps don't report these data. It should be as easy as having
them send in update_active_status queries with new_user_input=true.
* The semantics of this should be better documented (e.g. the
management script should print out the spec above)x.
(imported from commit ec8b2dc96b180e1951df00490707ae916887178e)
The new version is more accurate (doesn't rely on UserMessage IDs
being sorted, which they aren't necessarily) and simpler.
(imported from commit 671dd89dc8881ae2dcb8d0e804fd65458e074a29)
Zev Benjamin
Jessica McKellar
Leo Franchi
Waseem Daher
Steve Howell
Tim Abbott
Scott Feeney
Kevin Mehall