Using Flask and Pandas to stream response data to excel

I am using a combination of Flask and Pandas to return a created Excel file. The data is read in as chunks using the Pandas read_sql method like so:

chunks = pd.read_sql(query_string, conn_sql_server, chunksize=1000)

As the returning results from the query can be very large (around 800,000 rows) I make use of Flask's Streaming with Context

return Response(stream_with_context(generate_function(data_chunk, conn_sql_server)), headers=headers)

Where my generate_function is as follows:

    def generate_function(self, data_chunk, conn_sql_server):
    logger.info('Reading all SQL Server Table')
    try:
        is_first_iteration = True
        response = ''
        is_complete = False
        total_rows = 0
        output = BytesIO()
        writer = pd.ExcelWriter(output, engine='xlsxwriter')
        for chunk in data_chunk:
            if total_rows == self.top_data or total_rows >= self.limit_rows_xlsx or total_rows == self.num_total_count:
                writer.save()
                output.seek(0)
                response = output.getvalue()
                yield response

            chunk.to_excel(writer, index=False,
                          sheet_name='Sheet1', encoding='utf-8')

            total_rows = total_rows + len(chunk)

            yield chunk
    except Exception as e:
        logger.error(f'Error formatting dataframe to xlsx: {str(e)}')
        raise FormatDataframeToXlsx('Error formatting data to xlsx')
    finally:
        if conn_sql_server is not None:
            conn_sql_server.close()

However this returns me nothing. The only other option I thought was to loop the chunks and create a dataframe and then yield the result however this occurs an Nginx timeout on the server:

        is_first_iteration = True
        response = ''
        is_complete = False
        total_rows = 0
        for chunk in data_chunk:
            if is_complete:
                break
            if is_first_iteration:
                data = chunk
                is_first_iteration = False
            else:
                data = data.append(chunk)
            total_rows = total_rows + len(chunk)
            if total_rows == self.top_data or total_rows >= self.limit_rows_xlsx or total_rows == self.num_total_count:
                if total_rows >= self.limit_rows_xlsx:
                    is_complete = True
                    data = data[:self.limit_rows_xlsx]
                output = BytesIO()
                writer = pd.ExcelWriter(output, engine='xlsxwriter')
                data.to_excel(writer, index=False,
                              sheet_name='Sheet1', encoding='utf-8')
                writer.save()
                output.seek(0)
                response = output.getvalue()
            yield response

Is there a more suited method to handling large amounts of data to be written to excel like this?