def instructors_over_time(self, request, format=None):
"""Cumulative number of instructor appearances on workshops over
time."""
badges = Badge.objects.instructor_badges()
qs = Person.objects.filter(badges__in=badges).annotate(
date=Min('award__awarded'),
count=Value(1, output_field=IntegerField())
).order_by('date')
filter = InstructorsOverTimeFilter(request.GET, queryset=qs)
serializer = InstructorsOverTimeSerializer(filter.qs, many=True)
# run a cumulative generator over the data
data = accumulate(serializer.data, self._add_counts)
# drop data for the same days by showing the last record for
# particular date
data = self._only_latest_date(data)
data = self.listify(data, request, format)
return Response(data)
def instructors_over_time(request):
'''Export JSON of count of instructors vs. time.'''
endpoint = '{}?{}'.format(reverse('api:reports-instructors-over-time'),
request.GET.urlencode())
context = {
'api_endpoint': endpoint,
'filter': InstructorsOverTimeFilter(request.GET),
'title': 'Instructors over time',
}
return render(request, 'reports/time_series.html', context)
def test_badge_non_iterable(self):
"""Regression test: ensure badges are correctly selected by filter."""
badges = Badge.objects.instructor_badges()
qs = Person.objects.annotate(
date=Min('award__awarded'),
count=Value(1, output_field=IntegerField())).order_by('date')
params = QueryDict("badges=1&badges=2")
filter_ = InstructorsOverTimeFilter(params, queryset=qs)
# would throw an error if the regression is still present
self.assertTrue(filter_.qs)