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-rw-r--r--src/booking/stats.py70
1 files changed, 34 insertions, 36 deletions
diff --git a/src/booking/stats.py b/src/booking/stats.py
index 47de80b..bdb478a 100644
--- a/src/booking/stats.py
+++ b/src/booking/stats.py
@@ -1,5 +1,5 @@
##############################################################################
-# Copyright (c) 2018 Parker Berberian, Sawyer Bergeron, and others.
+# Copyright (c) 2020 Parker Berberian, Sawyer Bergeron, Sean Smith and others.
#
# All rights reserved. This program and the accompanying materials
# are made available under the terms of the Apache License, Version 2.0
@@ -7,7 +7,7 @@
# http://www.apache.org/licenses/LICENSE-2.0
##############################################################################
from booking.models import Booking
-import datetime
+from datetime import datetime, timedelta
import pytz
@@ -18,43 +18,41 @@ class StatisticsManager(object):
"""
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
+ Gathers all active bookings that fall in interval [(now - span), (now + 1 week)].
+ x data points are every 12 hours
+ y values are the integer number of bookings/users active at 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]))
+
+ now = datetime.now(pytz.utc)
+ delta = timedelta(days=span)
+ start = now - delta
+ end = now + timedelta(weeks=1)
+
+ bookings = Booking.objects.filter(
+ start__lte=end,
+ end__gte=start
+ ).prefetch_related("collaborators")
+
+ # get data
+ while start <= end:
+ active_users = 0
+
+ books = bookings.filter(
+ start__lte=start,
+ end__gte=start
+ ).prefetch_related("collaborators")
+
+ for booking in books:
+ active_users += booking.collaborators.all().count() + 1
+
+ x.append(str(start))
+ y.append(books.count())
+ users.append(active_users)
+
+ start += timedelta(hours=12)
return {"booking": [x, y], "user": [x, users]}