def test_get_election0_xlsx(self):
        response = self.client.get(
            reverse('results-export'),
            { 'election': str(Election.objects.get(name='Election 0').id) }
        )

        self.assertEqual(response.status_code, 200)        

        self.assertEqual(
            response['Content-Disposition'],
            'attachment; filename="Election 0 Results.xlsx"'
        )

        wb = openpyxl.load_workbook(io.BytesIO(response.content))

        self.assertEqual(len(wb.worksheets), 1)

        # Check first worksheet.
        ws = wb.worksheets[0]

        self.assertEqual(wb.sheetnames[0], 'Election 0')

        row_count = ws.max_row
        col_count = ws.max_column
        self.assertEqual(row_count, 25)
        self.assertEqual(col_count, 5)

        self.assertEqual(str(ws.cell(1, 1).value), 'Election 0 Results')

        self.assertEqual(str(ws.cell(2, 1).value), 'Candidates')

        cellContents = [
            'Position 0',
            'Party 0',
            '0, 0',
            'Party 1',
            '3, 3',
            'Party 2',
            'None',
            'Position 1',
            'Party 0',
            '1, 1',
            'Party 1',
            '4, 4',
            'Party 2',
            'None',
            'Position 2',
            'Party 0',
            '2, 2',
            'Party 1',
            '5, 5',
            'Party 2',
            'None'
        ]
        for cellIndex, content in enumerate(cellContents, 5):
            self.assertEqual(str(ws.cell(cellIndex, 1).value), content) 

        self.assertEqual(str(ws.cell(2, 2).value), 'Number of Votes')

        self.assertEqual(str(ws.cell(3, 2).value), '0')

        self.assertEqual(str(ws.cell(4, 2).value), '0') # Section

        self.assertEqual(str(ws.cell(7, 2).value), '1')
        self.assertEqual(str(ws.cell(9, 2).value), '0')
        self.assertEqual(str(ws.cell(11, 2).value), 'N/A')
        self.assertEqual(str(ws.cell(14, 2).value), '2')
        self.assertEqual(str(ws.cell(16, 2).value), '0')
        self.assertEqual(str(ws.cell(18, 2).value), 'N/A')
        self.assertEqual(str(ws.cell(21, 2).value), '0')
        self.assertEqual(str(ws.cell(23, 2).value), '0')
        self.assertEqual(str(ws.cell(25, 2).value), 'N/A')

        self.assertEqual(str(ws.cell(4, 3).value), '1') # Section

        self.assertEqual(str(ws.cell(7, 3).value), '0')
        self.assertEqual(str(ws.cell(9, 3).value), '1')
        self.assertEqual(str(ws.cell(11, 2).value), 'N/A')
        self.assertEqual(str(ws.cell(14, 3).value), '0')
        self.assertEqual(str(ws.cell(16, 3).value), '0')
        self.assertEqual(str(ws.cell(18, 2).value), 'N/A')
        self.assertEqual(str(ws.cell(21, 3).value), '1')
        self.assertEqual(str(ws.cell(23, 3).value), '0')
        self.assertEqual(str(ws.cell(25, 2).value), 'N/A')

        self.assertEqual(str(ws.cell(3, 4).value), '1')

        self.assertEqual(str(ws.cell(4, 4).value), '2') # Section

        self.assertEqual(str(ws.cell(7, 4).value), '0')
        self.assertEqual(str(ws.cell(9, 4).value), '0')
        self.assertEqual(str(ws.cell(11, 2).value), 'N/A')
        self.assertEqual(str(ws.cell(14, 4).value), '0')
        self.assertEqual(str(ws.cell(16, 4).value), '1')
        self.assertEqual(str(ws.cell(18, 2).value), 'N/A')
        self.assertEqual(str(ws.cell(21, 4).value), '0')
        self.assertEqual(str(ws.cell(23, 4).value), '1')
        self.assertEqual(str(ws.cell(25, 2).value), 'N/A')

        self.assertEqual(str(ws.cell(3, 5).value), 'Total Votes')
        self.assertEqual(str(ws.cell(7, 5).value), '1')
        self.assertEqual(str(ws.cell(9, 5).value), '1')
        self.assertEqual(str(ws.cell(11, 2).value), 'N/A')
        self.assertEqual(str(ws.cell(14, 5).value), '2')
        self.assertEqual(str(ws.cell(16, 5).value), '1')
        self.assertEqual(str(ws.cell(18, 2).value), 'N/A')
        self.assertEqual(str(ws.cell(21, 5).value), '1')
        self.assertEqual(str(ws.cell(23, 5).value), '1')
        self.assertEqual(str(ws.cell(25, 2).value), 'N/A')
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)