zulip/zerver/lib/statistics.py

94 lines
3.6 KiB
Python

# -*- coding: utf-8 -*-
from __future__ import absolute_import
from zerver.models import UserProfile, Realm, UserActivity, UserActivityInterval
from django.utils.timezone import utc
from datetime import timedelta, datetime
from itertools import chain
def median(data):
data = sorted(data)
size = len(data)
if size % 2 == 1:
return data[size//2]
else:
before = size//2 - 1
after = size//2
return (data[before] + data[after]) / 2.0
def active_users_to_measure():
# Return a list of active users we want to count towards various
# statistics. This eliminates bots, @zulip.com, @customer29.invalid and customer3.invalid
exclude_realms = ["zulip.com", "customer29.invalid", "customer3.invalid"]
return UserProfile.objects.filter(is_bot=False, is_active=True) \
.exclude(realm__domain__in=exclude_realms) \
.select_related()
# Return a set of users who have done some activity in the given timespan--that is,
# we have a UserActivity row for them. This counts pointer moves, flag updates, etc.
def users_active_between(begin, end):
activities = UserActivity.objects.filter(last_visit__gt=begin, last_visit__lt=end)
active = set([a.user_profile for a in activities])
interesting_users = set(active_users_to_measure())
return active.intersection(interesting_users)
# Return the amount of Zulip usage for this user between the two
# given dates
def seconds_usage_between(user_profile, begin, end):
intervals = UserActivityInterval.objects.filter(user_profile=user_profile, end__gte=begin, start__lte=end)
duration = timedelta(0)
for interval in intervals:
start = max(begin, interval.start)
finish = min(end, interval.end)
duration += finish-start
return duration
# Return a list of how many seconds each user has been engaging with the app on a given day
def seconds_active_during_day(day):
begin_day = day.replace(hour=0, minute=0, second=0, microsecond=0, tzinfo=utc)
end_day = day.replace(hour=23, minute=59, second=59, microsecond=0, tzinfo=utc)
active_users = users_active_between(begin_day, end_day)
# Exclude Friday CUSTOMER4 activity numbers
if day.weekday() == 4:
active_users = [u for u in active_users if u.realm.domain != 'users.customer4.invalid']
return [seconds_usage_between(user, begin_day, end_day).total_seconds() for user in active_users]
def calculate_stats(data):
if len(data) == 0:
return 0, 0
mean_data = sum(data) / len(data)
median_data = median(data)
return {'mean': str(timedelta(seconds=mean_data)), 'median': str(timedelta(seconds=median_data)), '# data points': len(data)}
# Return an info dict {mean: , median} containing the mean/median seconds users were active on a given day
def activity_averages_during_day(day):
seconds_active = seconds_active_during_day(day)
return calculate_stats(seconds_active)
# Returns an info dict {mean: , median} with engagement numbers for all users according
# to active_users_to_measure. This will ignore weekends, and ignore users.customer4.invalid
# on Fridays
def activity_averages_between(begin, end, by_day=True):
seconds_active = {}
for i in range((end - begin).days):
day = begin + timedelta(days=i)
# Ignore weekends
if day.weekday() in [5, 6]:
continue
seconds_active[day] = seconds_active_during_day(day)
if by_day:
return dict((day, calculate_stats(values)) for day, values in seconds_active.iteritems())
else:
return calculate_stats(list(chain.from_iterable(seconds_active.values())))