def setUpTestData(cls):
        batch_num = 0
        section_num = 0
        voter_num = 0
        party_num = 0
        position_num = 0
        candidate_num = 0
        num_elections = 2
        voters = list()
        positions = dict()
        for i in range(num_elections):
            election = Election.objects.create(name='Election {}'.format(i))
            positions[str(election.name)] = list()

            num_batches = 2
            for j in range(num_batches):
                batch = Batch.objects.create(year=batch_num, election=election)
                batch_num += 1

                num_sections = 2 if j == 0 else 1
                for k in range(num_sections):
                    section = Section.objects.create(
                        section_name=str(section_num)
                    )
                    section_num += 1

                    num_students = 2
                    for l in range(num_students):
                        voter = User.objects.create(
                            username='user{}'.format(voter_num),
                            first_name=str(voter_num),
                            last_name=str(voter_num),
                            type=UserType.VOTER
                        )
                        voter.set_password('voter')
                        voter.save()
                        voter_num += 1

                        VoterProfile.objects.create(
                            user=voter,
                            batch=batch,
                            section=section
                        )

                        voters.append(voter)

            num_positions = 3
            for i in range(num_positions):
                position = CandidatePosition.objects.create(
                    position_name='Position {}'.format(position_num),
                    election=election
                )

                positions[str(election.name)].append(position)

                position_num += 1

            num_parties = 3
            for j in range(num_parties):
                party = CandidateParty.objects.create(
                    party_name='Party {}'.format(party_num),
                    election=election
                )
                party_num += 1

                if j != 2:  # Let every third party have no candidates.
                    num_positions = 3
                    for k in range(num_positions):
                        position = positions[str(election.name)][k]

                        candidate = Candidate.objects.create(
                            user=voters[candidate_num],
                            party=party,
                            position=position,
                            election=election
                        )

                        Vote.objects.create(
                            user=voters[candidate_num],
                            candidate=candidate,
                            election=election
                        )

                        candidate_num += 1

        # Let's give one candidate an additional vote to really make sure that
        # we all got the correct number of votes.
        Vote.objects.create(
            user=voters[0],
            # NOTE: The voter in voter[1] is a Position 1 candidate of
            #       Party 1, where the voter in voter[0] is a member.
            candidate=Candidate.objects.get(user=voters[1]),
            election=Election.objects.get(name='Election 0')
        )

        _admin = User.objects.create(username='admin', type=UserType.ADMIN)
        _admin.set_password('root')
        _admin.save()
def run(
            self, field, query_string='', query_dsl='',
            supported_charts='table', start_time='', end_time='', limit=10):
        """Run the aggregation.

        Args:
            field (str): this denotes the event attribute that is used
                for aggregation.
            query_string (str): the query field to run on all documents prior to
                aggregating the results.
            query_dsl (str): the query DSL field to run on all documents prior
                to aggregating the results. Either a query string or a query
                DSL has to be present.
            supported_charts: Chart type to render. Defaults to table.
            start_time: Optional ISO formatted date string that limits the time
                range for the aggregation.
            end_time: Optional ISO formatted date string that limits the time
                range for the aggregation.
            limit (int): How many buckets to return, defaults to 10.

        Returns:
            Instance of interface.AggregationResult with aggregation result.

        Raises:
            ValueError: if neither query_string or query_dsl is provided.
        """
        if not (query_string or query_dsl):
            raise ValueError('Both query_string and query_dsl are missing')

        self.field = field
        formatted_field_name = self.format_field_by_type(field)

        aggregation_spec = get_spec(
            field=formatted_field_name, limit=limit, query=query_string,
            query_dsl=query_dsl)

        aggregation_spec = self._add_query_to_aggregation_spec(
            aggregation_spec, start_time=start_time, end_time=end_time)

        # Encoding information for Vega-Lite.
        encoding = {
            'x': {
                'field': field,
                'type': 'nominal',
                'sort': {
                    'op': 'sum',
                    'field': 'count',
                    'order': 'descending'
                }
            },
            'y': {'field': 'count', 'type': 'quantitative'},
            'tooltip': [
                {'field': field, 'type': 'nominal'},
                {'field': 'count', 'type': 'quantitative'}],
        }

        response = self.opensearch_aggregation(aggregation_spec)
        aggregations = response.get('aggregations', {})
        aggregation = aggregations.get('aggregation', {})

        buckets = aggregation.get('buckets', [])
        values = []
        for bucket in buckets:
            d = {
                field: bucket.get('key', 'N/A'),
                'count': bucket.get('doc_count', 0)
            }
            values.append(d)

        if query_string:
            extra_query_url = 'AND {0:s}'.format(query_string)
        else:
            extra_query_url = ''

        return interface.AggregationResult(
            encoding=encoding, values=values, chart_type=supported_charts,
            sketch_url=self._sketch_url, field=field,
            extra_query_url=extra_query_url)