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