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 groupby(cls, dataset, dimensions, container_type, group_type, **kwargs):
        # Get dimensions information
        dimensions = [dataset.get_dimension(d).name for d in dimensions]
        kdims = [kdim for kdim in dataset.kdims if kdim not in dimensions]

        # Update the kwargs appropriately for Element group types
        group_kwargs = {}
        group_type = dict if group_type == 'raw' else group_type
        if issubclass(group_type, Element):
            group_kwargs.update(util.get_param_values(dataset))
            group_kwargs['kdims'] = kdims
        group_kwargs.update(kwargs)

        # Propagate dataset
        group_kwargs['dataset'] = dataset.dataset

        # Find all the keys along supplied dimensions
        keys = product(*(dataset.data[dimensions[0]].unique().values_host for d in dimensions))

        # Iterate over the unique entries applying selection masks
        grouped_data = []
        for unique_key in util.unique_iterator(keys):
            group_data = dataset.select(**dict(zip(dimensions, unique_key)))
            if not len(group_data):
                continue
            group_data = group_type(group_data, **group_kwargs)
            grouped_data.append((unique_key, group_data))

        if issubclass(container_type, NdMapping):
            with item_check(False), sorted_context(False):
                kdims = [dataset.get_dimension(d) for d in dimensions]
                return container_type(grouped_data, kdims=kdims)
        else:
            return container_type(grouped_data)