mirror of https://github.com/zulip/zulip.git
138 lines
5.3 KiB
Python
138 lines
5.3 KiB
Python
# -*- coding: utf-8 -*-
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from __future__ import absolute_import
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from __future__ import division
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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 typing import Any
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from datetime import datetime, timedelta
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from itertools import chain
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from six.moves import range
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import six
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def median(data):
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# type: (List[float]) -> float
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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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# type: () -> List[UserProfile]
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# Return a list of active users we want to count towards various
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# statistics.
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return UserProfile.objects.filter(is_bot=False, is_active=True).select_related()
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def users_who_sent_between(begin, end):
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# type: (datetime, datetime) -> Set[int]
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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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# type: () -> Set[int]
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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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# type: () -> List[UserProfile]
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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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# type: (datetime, datetime) -> List[UserProfile]
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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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# type: (UserProfile, datetime, datetime) -> timedelta
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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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# type: (datetime) -> List[float]
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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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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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# type: (datetime) -> List[UserProfile]
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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 u.id not in today_senders]
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def calculate_stats(data, all_users):
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# type: (List[float], List[UserProfile]) -> Dict[str, Any]
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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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# type: (datetime) -> Dict[str, Any]
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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.
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def activity_averages_between(begin, end, by_day=True):
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# type: (datetime, datetime, bool) -> Dict[str, Any]
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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((str(day), calculate_stats(values, all_users=users_to_measure))
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for day, values in six.iteritems(seconds_active))
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else:
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return calculate_stats(list(chain.from_iterable(seconds_active.values())), # type: ignore # chain.from_iterable needs overload
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all_users=users_to_measure)
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