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https://github.com/zulip/zulip.git
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3b7bf691e7
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)
130 lines
5.2 KiB
Python
130 lines
5.2 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, Message
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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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users_who_sent_query = Message.objects.select_related("sender") \
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.exclude(sending_client__name__contains="mirror") \
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.exclude(sending_client__name__contains="API")
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def active_users():
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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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"ios_appreview.zulip.com", "wdaher.com", "customer30.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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def users_who_sent_between(begin, end):
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sender_objs = users_who_sent_query.filter(pub_date__gt=begin, pub_date__lt=end) \
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.values("sender__id")
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return set(s["sender__id"] for s in sender_objs)
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def users_who_sent_ever():
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return set(s["sender__id"] for s in users_who_sent_query.values("sender__id"))
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def active_users_to_measure():
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senders = users_who_sent_ever()
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return [u for u in active_users() if u.id in senders]
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def active_users_who_sent_between(begin, end):
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senders = users_who_sent_between(begin, end)
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return [u for u in active_users() if u.id in senders]
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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 = active_users_to_measure()
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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 users_active_nosend_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 = active_users_to_measure()
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today_senders = users_who_sent_between(begin_day, end_day)
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today_users = []
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for user_profile in active_users:
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intervals = UserActivityInterval.objects.filter(user_profile=user_profile,
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end__gte=begin_day,
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start__lte=end_day)
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if len(intervals) != 0:
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today_users.append(user_profile)
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return [u for u in today_users if not u.id in today_senders]
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def calculate_stats(data, all_users):
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if len(data) == 0:
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return {"# data points": 0}
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active_user_count = len([x for x in data if x > 1])
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mean_data = sum(data) / active_user_count
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median_data = median([x for x in data if x > 1])
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return {'active users': active_user_count,
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'total users': len(all_users),
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'mean': str(timedelta(seconds=mean_data)),
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'median': str(timedelta(seconds=median_data)),
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'# 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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users_to_measure = active_users_to_measure()
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seconds_active = seconds_active_during_day(day)
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return calculate_stats(seconds_active, all_users=users_to_measure)
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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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users_to_measure = active_users_to_measure()
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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, all_users=users_to_measure))
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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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all_users=users_to_measure)
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