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##############################################################################
# Copyright (c) 2018 Parker Berberian, Sawyer Bergeron, and others.
#
# All rights reserved. This program and the accompanying materials
# are made available under the terms of the Apache License, Version 2.0
# which accompanies this distribution, and is available at
# http://www.apache.org/licenses/LICENSE-2.0
##############################################################################
from booking.models import Booking
import datetime
import pytz
class StatisticsManager(object):
@staticmethod
def getContinuousBookingTimeSeries(span=28):
"""
Calculate Booking usage data points.
Will return a dictionary of names and 2-D array of x and y data points.
e.g. {"plot1": [["x1", "x2", "x3"],["y1", "y2", "y3]]}
x values will be dates in string
every change (booking start / end) will be reflected,
instead of one data point per day
y values are the integer number of bookings/users active at
some point in the given date span is the number of days to plot.
The last x value will always be the current time
"""
data = []
x = []
y = []
users = []
now = datetime.datetime.now(pytz.utc)
delta = datetime.timedelta(days=span)
end = now - delta
bookings = Booking.objects.filter(start__lte=now, end__gte=end).prefetch_related("collaborators")
for booking in bookings: # collect data from each booking
user_list = [u.pk for u in booking.collaborators.all()]
user_list.append(booking.owner.pk)
data.append((booking.start, 1, user_list))
data.append((booking.end, -1, user_list))
# sort based on time
data.sort(key=lambda i: i[0])
# collect data
count = 0
active_users = {}
for datum in data:
x.append(str(datum[0])) # time
count += datum[1] # booking count
y.append(count)
for pk in datum[2]: # maintain count of each user's active bookings
active_users[pk] = active_users.setdefault(pk, 0) + datum[1]
if active_users[pk] == 0:
del active_users[pk]
users.append(len([x for x in active_users.values() if x > 0]))
return {"booking": [x, y], "user": [x, users]}
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