def on_get(req, resp): print(req.params) shopfloor_id = req.params.get('shopfloorid') period_type = req.params.get('periodtype') base_start_datetime_local = req.params.get('baseperiodstartdatetime') base_end_datetime_local = req.params.get('baseperiodenddatetime') reporting_start_datetime_local = req.params.get('reportingperiodstartdatetime') reporting_end_datetime_local = req.params.get('reportingperiodenddatetime') ################################################################################################################ # Step 1: valid parameters ################################################################################################################ if shopfloor_id is None: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_SHOPFLOOR_ID') else: shopfloor_id = str.strip(shopfloor_id) if not shopfloor_id.isdigit() or int(shopfloor_id) <= 0: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_SHOPFLOOR_ID') if period_type is None: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_PERIOD_TYPE') else: period_type = str.strip(period_type) if period_type not in ['hourly', 'daily', 'monthly', 'yearly']: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_PERIOD_TYPE') timezone_offset = int(config.utc_offset[1:3]) * 60 + int(config.utc_offset[4:6]) if config.utc_offset[0] == '-': timezone_offset = -timezone_offset base_start_datetime_utc = None if base_start_datetime_local is not None and len(str.strip(base_start_datetime_local)) > 0: base_start_datetime_local = str.strip(base_start_datetime_local) try: base_start_datetime_utc = datetime.strptime(base_start_datetime_local, '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ timedelta(minutes=timezone_offset) except ValueError: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_BASE_PERIOD_BEGINS_DATETIME") base_end_datetime_utc = None if base_end_datetime_local is not None and len(str.strip(base_end_datetime_local)) > 0: base_end_datetime_local = str.strip(base_end_datetime_local) try: base_end_datetime_utc = datetime.strptime(base_end_datetime_local, '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ timedelta(minutes=timezone_offset) except ValueError: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_BASE_PERIOD_ENDS_DATETIME") if base_start_datetime_utc is not None and base_end_datetime_utc is not None and \ base_start_datetime_utc >= base_end_datetime_utc: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_BASE_PERIOD_ENDS_DATETIME') if reporting_start_datetime_local is None: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_REPORTING_PERIOD_BEGINS_DATETIME") else: reporting_start_datetime_local = str.strip(reporting_start_datetime_local) try: reporting_start_datetime_utc = datetime.strptime(reporting_start_datetime_local, '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ timedelta(minutes=timezone_offset) except ValueError: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_REPORTING_PERIOD_BEGINS_DATETIME") if reporting_end_datetime_local is None: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_REPORTING_PERIOD_ENDS_DATETIME") else: reporting_end_datetime_local = str.strip(reporting_end_datetime_local) try: reporting_end_datetime_utc = datetime.strptime(reporting_end_datetime_local, '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ timedelta(minutes=timezone_offset) except ValueError: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_REPORTING_PERIOD_ENDS_DATETIME") if reporting_start_datetime_utc >= reporting_end_datetime_utc: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_REPORTING_PERIOD_ENDS_DATETIME') ################################################################################################################ # Step 2: query the shopfloor ################################################################################################################ cnx_system = mysql.connector.connect(**config.myems_system_db) cursor_system = cnx_system.cursor() cnx_energy = mysql.connector.connect(**config.myems_energy_db) cursor_energy = cnx_energy.cursor() cnx_energy_baseline = mysql.connector.connect(**config.myems_energy_baseline_db) cursor_energy_baseline = cnx_energy_baseline.cursor() cnx_historical = mysql.connector.connect(**config.myems_historical_db) cursor_historical = cnx_historical.cursor() cursor_system.execute(" SELECT id, name, area, cost_center_id " " FROM tbl_shopfloors " " WHERE id = %s ", (shopfloor_id,)) row_shopfloor = cursor_system.fetchone() if row_shopfloor is None: if cursor_system: cursor_system.close() if cnx_system: cnx_system.disconnect() if cursor_energy: cursor_energy.close() if cnx_energy: cnx_energy.disconnect() if cursor_energy_baseline: cursor_energy_baseline.close() if cnx_energy_baseline: cnx_energy_baseline.disconnect() if cnx_historical: cnx_historical.close() if cursor_historical: cursor_historical.disconnect() raise falcon.HTTPError(falcon.HTTP_404, title='API.NOT_FOUND', description='API.SHOPFLOOR_NOT_FOUND') shopfloor = dict() shopfloor['id'] = row_shopfloor[0] shopfloor['name'] = row_shopfloor[1] shopfloor['area'] = row_shopfloor[2] shopfloor['cost_center_id'] = row_shopfloor[3] ################################################################################################################ # Step 3: query energy categories ################################################################################################################ energy_category_set = set() # query energy categories in base period cursor_energy.execute(" SELECT DISTINCT(energy_category_id) " " FROM tbl_shopfloor_input_category_hourly " " WHERE shopfloor_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s ", (shopfloor['id'], base_start_datetime_utc, base_end_datetime_utc)) rows_energy_categories = cursor_energy.fetchall() if rows_energy_categories is not None or len(rows_energy_categories) > 0: for row_energy_category in rows_energy_categories: energy_category_set.add(row_energy_category[0]) # query energy categories in reporting period cursor_energy.execute(" SELECT DISTINCT(energy_category_id) " " FROM tbl_shopfloor_input_category_hourly " " WHERE shopfloor_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s ", (shopfloor['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) rows_energy_categories = cursor_energy.fetchall() if rows_energy_categories is not None or len(rows_energy_categories) > 0: for row_energy_category in rows_energy_categories: energy_category_set.add(row_energy_category[0]) # query all energy categories in base period and reporting period cursor_system.execute(" SELECT id, name, unit_of_measure, kgce, kgco2e " " FROM tbl_energy_categories " " ORDER BY id ", ) rows_energy_categories = cursor_system.fetchall() if rows_energy_categories is None or len(rows_energy_categories) == 0: if cursor_system: cursor_system.close() if cnx_system: cnx_system.disconnect() if cursor_energy: cursor_energy.close() if cnx_energy: cnx_energy.disconnect() if cursor_energy_baseline: cursor_energy_baseline.close() if cnx_energy_baseline: cnx_energy_baseline.disconnect() if cnx_historical: cnx_historical.close() if cursor_historical: cursor_historical.disconnect() raise falcon.HTTPError(falcon.HTTP_404, title='API.NOT_FOUND', description='API.ENERGY_CATEGORY_NOT_FOUND') energy_category_dict = dict() for row_energy_category in rows_energy_categories: if row_energy_category[0] in energy_category_set: energy_category_dict[row_energy_category[0]] = {"name": row_energy_category[1], "unit_of_measure": row_energy_category[2], "kgce": row_energy_category[3], "kgco2e": row_energy_category[4]} ################################################################################################################ # Step 4: query associated sensors ################################################################################################################ point_list = list() cursor_system.execute(" SELECT p.id, p.name, p.units, p.object_type " " FROM tbl_shopfloors st, tbl_sensors se, tbl_shopfloors_sensors ss, " " tbl_points p, tbl_sensors_points sp " " WHERE st.id = %s AND st.id = ss.shopfloor_id AND ss.sensor_id = se.id " " AND se.id = sp.sensor_id AND sp.point_id = p.id " " ORDER BY p.id ", (shopfloor['id'],)) rows_points = cursor_system.fetchall() if rows_points is not None and len(rows_points) > 0: for row in rows_points: point_list.append({"id": row[0], "name": row[1], "units": row[2], "object_type": row[3]}) ################################################################################################################ # Step 5: query associated points ################################################################################################################ cursor_system.execute(" SELECT p.id, p.name, p.units, p.object_type " " FROM tbl_shopfloors s, tbl_shopfloors_points sp, tbl_points p " " WHERE s.id = %s AND s.id = sp.shopfloor_id AND sp.point_id = p.id " " ORDER BY p.id ", (shopfloor['id'],)) rows_points = cursor_system.fetchall() if rows_points is not None and len(rows_points) > 0: for row in rows_points: point_list.append({"id": row[0], "name": row[1], "units": row[2], "object_type": row[3]}) ################################################################################################################ # Step 6: query base period energy saving ################################################################################################################ base = dict() if energy_category_set is not None and len(energy_category_set) > 0: for energy_category_id in energy_category_set: kgce = energy_category_dict[energy_category_id]['kgce'] kgco2e = energy_category_dict[energy_category_id]['kgco2e'] base[energy_category_id] = dict() base[energy_category_id]['timestamps'] = list() base[energy_category_id]['values_baseline'] = list() base[energy_category_id]['values_actual'] = list() base[energy_category_id]['values_saving'] = list() base[energy_category_id]['subtotal_baseline'] = Decimal(0.0) base[energy_category_id]['subtotal_actual'] = Decimal(0.0) base[energy_category_id]['subtotal_saving'] = Decimal(0.0) base[energy_category_id]['subtotal_in_kgce_baseline'] = Decimal(0.0) base[energy_category_id]['subtotal_in_kgce_actual'] = Decimal(0.0) base[energy_category_id]['subtotal_in_kgce_saving'] = Decimal(0.0) base[energy_category_id]['subtotal_in_kgco2e_baseline'] = Decimal(0.0) base[energy_category_id]['subtotal_in_kgco2e_actual'] = Decimal(0.0) base[energy_category_id]['subtotal_in_kgco2e_saving'] = Decimal(0.0) # query base period's energy baseline cursor_energy_baseline.execute(" SELECT start_datetime_utc, actual_value " " FROM tbl_shopfloor_input_category_hourly " " WHERE shopfloor_id = %s " " AND energy_category_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s " " ORDER BY start_datetime_utc ", (shopfloor['id'], energy_category_id, base_start_datetime_utc, base_end_datetime_utc)) rows_shopfloor_hourly = cursor_energy_baseline.fetchall() rows_shopfloor_periodically = utilities.aggregate_hourly_data_by_period(rows_shopfloor_hourly, base_start_datetime_utc, base_end_datetime_utc, period_type) for row_shopfloor_periodically in rows_shopfloor_periodically: current_datetime_local = row_shopfloor_periodically[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) if period_type == 'hourly': current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') elif period_type == 'daily': current_datetime = current_datetime_local.strftime('%Y-%m-%d') elif period_type == 'monthly': current_datetime = current_datetime_local.strftime('%Y-%m') elif period_type == 'yearly': current_datetime = current_datetime_local.strftime('%Y') baseline_value = Decimal(0.0) if row_shopfloor_periodically[1] is None \ else row_shopfloor_periodically[1] base[energy_category_id]['timestamps'].append(current_datetime) base[energy_category_id]['values_baseline'].append(baseline_value) base[energy_category_id]['subtotal_baseline'] += baseline_value base[energy_category_id]['subtotal_in_kgce_baseline'] += baseline_value * kgce base[energy_category_id]['subtotal_in_kgco2e_baseline'] += baseline_value * kgco2e # query base period's energy actual cursor_energy.execute(" SELECT start_datetime_utc, actual_value " " FROM tbl_shopfloor_input_category_hourly " " WHERE shopfloor_id = %s " " AND energy_category_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s " " ORDER BY start_datetime_utc ", (shopfloor['id'], energy_category_id, base_start_datetime_utc, base_end_datetime_utc)) rows_shopfloor_hourly = cursor_energy.fetchall() rows_shopfloor_periodically = utilities.aggregate_hourly_data_by_period(rows_shopfloor_hourly, base_start_datetime_utc, base_end_datetime_utc, period_type) for row_shopfloor_periodically in rows_shopfloor_periodically: current_datetime_local = row_shopfloor_periodically[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) if period_type == 'hourly': current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') elif period_type == 'daily': current_datetime = current_datetime_local.strftime('%Y-%m-%d') elif period_type == 'monthly': current_datetime = current_datetime_local.strftime('%Y-%m') elif period_type == 'yearly': current_datetime = current_datetime_local.strftime('%Y') actual_value = Decimal(0.0) if row_shopfloor_periodically[1] is None \ else row_shopfloor_periodically[1] base[energy_category_id]['values_actual'].append(actual_value) base[energy_category_id]['subtotal_actual'] += actual_value base[energy_category_id]['subtotal_in_kgce_actual'] += actual_value * kgce base[energy_category_id]['subtotal_in_kgco2e_actual'] += actual_value * kgco2e # calculate base period's energy savings for i in range(len(base[energy_category_id]['values_baseline'])): base[energy_category_id]['values_saving'].append( base[energy_category_id]['values_baseline'][i] - base[energy_category_id]['values_actual'][i]) base[energy_category_id]['subtotal_saving'] = \ base[energy_category_id]['subtotal_baseline'] - \ base[energy_category_id]['subtotal_actual'] base[energy_category_id]['subtotal_in_kgce_saving'] = \ base[energy_category_id]['subtotal_in_kgce_baseline'] - \ base[energy_category_id]['subtotal_in_kgce_actual'] base[energy_category_id]['subtotal_in_kgco2e_saving'] = \ base[energy_category_id]['subtotal_in_kgco2e_baseline'] - \ base[energy_category_id]['subtotal_in_kgco2e_actual'] ################################################################################################################ # Step 7: query reporting period energy saving ################################################################################################################ reporting = dict() if energy_category_set is not None and len(energy_category_set) > 0: for energy_category_id in energy_category_set: kgce = energy_category_dict[energy_category_id]['kgce'] kgco2e = energy_category_dict[energy_category_id]['kgco2e'] reporting[energy_category_id] = dict() reporting[energy_category_id]['timestamps'] = list() reporting[energy_category_id]['values_baseline'] = list() reporting[energy_category_id]['values_actual'] = list() reporting[energy_category_id]['values_saving'] = list() reporting[energy_category_id]['subtotal_baseline'] = Decimal(0.0) reporting[energy_category_id]['subtotal_actual'] = Decimal(0.0) reporting[energy_category_id]['subtotal_saving'] = Decimal(0.0) reporting[energy_category_id]['subtotal_in_kgce_baseline'] = Decimal(0.0) reporting[energy_category_id]['subtotal_in_kgce_actual'] = Decimal(0.0) reporting[energy_category_id]['subtotal_in_kgce_saving'] = Decimal(0.0) reporting[energy_category_id]['subtotal_in_kgco2e_baseline'] = Decimal(0.0) reporting[energy_category_id]['subtotal_in_kgco2e_actual'] = Decimal(0.0) reporting[energy_category_id]['subtotal_in_kgco2e_saving'] = Decimal(0.0) # query reporting period's energy baseline cursor_energy_baseline.execute(" SELECT start_datetime_utc, actual_value " " FROM tbl_shopfloor_input_category_hourly " " WHERE shopfloor_id = %s " " AND energy_category_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s " " ORDER BY start_datetime_utc ", (shopfloor['id'], energy_category_id, reporting_start_datetime_utc, reporting_end_datetime_utc)) rows_shopfloor_hourly = cursor_energy_baseline.fetchall() rows_shopfloor_periodically = utilities.aggregate_hourly_data_by_period(rows_shopfloor_hourly, reporting_start_datetime_utc, reporting_end_datetime_utc, period_type) for row_shopfloor_periodically in rows_shopfloor_periodically: current_datetime_local = row_shopfloor_periodically[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) if period_type == 'hourly': current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') elif period_type == 'daily': current_datetime = current_datetime_local.strftime('%Y-%m-%d') elif period_type == 'monthly': current_datetime = current_datetime_local.strftime('%Y-%m') elif period_type == 'yearly': current_datetime = current_datetime_local.strftime('%Y') baseline_value = Decimal(0.0) if row_shopfloor_periodically[1] is None \ else row_shopfloor_periodically[1] reporting[energy_category_id]['timestamps'].append(current_datetime) reporting[energy_category_id]['values_baseline'].append(baseline_value) reporting[energy_category_id]['subtotal_baseline'] += baseline_value reporting[energy_category_id]['subtotal_in_kgce_baseline'] += baseline_value * kgce reporting[energy_category_id]['subtotal_in_kgco2e_baseline'] += baseline_value * kgco2e # query reporting period's energy actual cursor_energy.execute(" SELECT start_datetime_utc, actual_value " " FROM tbl_shopfloor_input_category_hourly " " WHERE shopfloor_id = %s " " AND energy_category_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s " " ORDER BY start_datetime_utc ", (shopfloor['id'], energy_category_id, reporting_start_datetime_utc, reporting_end_datetime_utc)) rows_shopfloor_hourly = cursor_energy.fetchall() rows_shopfloor_periodically = utilities.aggregate_hourly_data_by_period(rows_shopfloor_hourly, reporting_start_datetime_utc, reporting_end_datetime_utc, period_type) for row_shopfloor_periodically in rows_shopfloor_periodically: current_datetime_local = row_shopfloor_periodically[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) if period_type == 'hourly': current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') elif period_type == 'daily': current_datetime = current_datetime_local.strftime('%Y-%m-%d') elif period_type == 'monthly': current_datetime = current_datetime_local.strftime('%Y-%m') elif period_type == 'yearly': current_datetime = current_datetime_local.strftime('%Y') actual_value = Decimal(0.0) if row_shopfloor_periodically[1] is None \ else row_shopfloor_periodically[1] reporting[energy_category_id]['values_actual'].append(actual_value) reporting[energy_category_id]['subtotal_actual'] += actual_value reporting[energy_category_id]['subtotal_in_kgce_actual'] += actual_value * kgce reporting[energy_category_id]['subtotal_in_kgco2e_actual'] += actual_value * kgco2e # calculate reporting period's energy savings for i in range(len(reporting[energy_category_id]['values_baseline'])): reporting[energy_category_id]['values_saving'].append( reporting[energy_category_id]['values_baseline'][i] - reporting[energy_category_id]['values_actual'][i]) reporting[energy_category_id]['subtotal_saving'] = \ reporting[energy_category_id]['subtotal_baseline'] - \ reporting[energy_category_id]['subtotal_actual'] reporting[energy_category_id]['subtotal_in_kgce_saving'] = \ reporting[energy_category_id]['subtotal_in_kgce_baseline'] - \ reporting[energy_category_id]['subtotal_in_kgce_actual'] reporting[energy_category_id]['subtotal_in_kgco2e_saving'] = \ reporting[energy_category_id]['subtotal_in_kgco2e_baseline'] - \ reporting[energy_category_id]['subtotal_in_kgco2e_actual'] ################################################################################################################ # Step 8: query tariff data ################################################################################################################ parameters_data = dict() parameters_data['names'] = list() parameters_data['timestamps'] = list() parameters_data['values'] = list() if energy_category_set is not None and len(energy_category_set) > 0: for energy_category_id in energy_category_set: energy_category_tariff_dict = utilities.get_energy_category_tariffs(shopfloor['cost_center_id'], energy_category_id, reporting_start_datetime_utc, reporting_end_datetime_utc) tariff_timestamp_list = list() tariff_value_list = list() for k, v in energy_category_tariff_dict.items(): # convert k from utc to local k = k + timedelta(minutes=timezone_offset) tariff_timestamp_list.append(k.isoformat()[0:19][0:19]) tariff_value_list.append(v) parameters_data['names'].append('TARIFF-' + energy_category_dict[energy_category_id]['name']) parameters_data['timestamps'].append(tariff_timestamp_list) parameters_data['values'].append(tariff_value_list) ################################################################################################################ # Step 9: query associated sensors and points data ################################################################################################################ for point in point_list: point_values = [] point_timestamps = [] if point['object_type'] == 'ANALOG_VALUE': query = (" SELECT utc_date_time, actual_value " " FROM tbl_analog_value " " WHERE point_id = %s " " AND utc_date_time BETWEEN %s AND %s " " ORDER BY utc_date_time ") cursor_historical.execute(query, (point['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) rows = cursor_historical.fetchall() if rows is not None and len(rows) > 0: for row in rows: current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') point_timestamps.append(current_datetime) point_values.append(row[1]) elif point['object_type'] == 'ENERGY_VALUE': query = (" SELECT utc_date_time, actual_value " " FROM tbl_energy_value " " WHERE point_id = %s " " AND utc_date_time BETWEEN %s AND %s " " ORDER BY utc_date_time ") cursor_historical.execute(query, (point['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) rows = cursor_historical.fetchall() if rows is not None and len(rows) > 0: for row in rows: current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') point_timestamps.append(current_datetime) point_values.append(row[1]) elif point['object_type'] == 'DIGITAL_VALUE': query = (" SELECT utc_date_time, actual_value " " FROM tbl_digital_value " " WHERE point_id = %s " " AND utc_date_time BETWEEN %s AND %s ") cursor_historical.execute(query, (point['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) rows = cursor_historical.fetchall() if rows is not None and len(rows) > 0: for row in rows: current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') point_timestamps.append(current_datetime) point_values.append(row[1]) parameters_data['names'].append(point['name'] + ' (' + point['units'] + ')') parameters_data['timestamps'].append(point_timestamps) parameters_data['values'].append(point_values) ################################################################################################################ # Step 10: construct the report ################################################################################################################ if cursor_system: cursor_system.close() if cnx_system: cnx_system.disconnect() if cursor_energy: cursor_energy.close() if cnx_energy: cnx_energy.disconnect() if cursor_energy_baseline: cursor_energy_baseline.close() if cnx_energy_baseline: cnx_energy_baseline.disconnect() result = dict() result['shopfloor'] = dict() result['shopfloor']['name'] = shopfloor['name'] result['shopfloor']['area'] = shopfloor['area'] result['base_period'] = dict() result['base_period']['names'] = list() result['base_period']['units'] = list() result['base_period']['timestamps'] = list() result['base_period']['values_saving'] = list() result['base_period']['subtotals_saving'] = list() result['base_period']['subtotals_in_kgce_saving'] = list() result['base_period']['subtotals_in_kgco2e_saving'] = list() result['base_period']['total_in_kgce_saving'] = Decimal(0.0) result['base_period']['total_in_kgco2e_saving'] = Decimal(0.0) if energy_category_set is not None and len(energy_category_set) > 0: for energy_category_id in energy_category_set: result['base_period']['names'].append(energy_category_dict[energy_category_id]['name']) result['base_period']['units'].append(energy_category_dict[energy_category_id]['unit_of_measure']) result['base_period']['timestamps'].append(base[energy_category_id]['timestamps']) result['base_period']['values_saving'].append(base[energy_category_id]['values_saving']) result['base_period']['subtotals_saving'].append(base[energy_category_id]['subtotal_saving']) result['base_period']['subtotals_in_kgce_saving'].append( base[energy_category_id]['subtotal_in_kgce_saving']) result['base_period']['subtotals_in_kgco2e_saving'].append( base[energy_category_id]['subtotal_in_kgco2e_saving']) result['base_period']['total_in_kgce_saving'] += base[energy_category_id]['subtotal_in_kgce_saving'] result['base_period']['total_in_kgco2e_saving'] += base[energy_category_id]['subtotal_in_kgco2e_saving'] result['reporting_period'] = dict() result['reporting_period']['names'] = list() result['reporting_period']['energy_category_ids'] = list() result['reporting_period']['units'] = list() result['reporting_period']['timestamps'] = list() result['reporting_period']['values_saving'] = list() result['reporting_period']['subtotals_saving'] = list() result['reporting_period']['subtotals_in_kgce_saving'] = list() result['reporting_period']['subtotals_in_kgco2e_saving'] = list() result['reporting_period']['subtotals_per_unit_area_saving'] = list() result['reporting_period']['increment_rates_saving'] = list() result['reporting_period']['total_in_kgce_saving'] = Decimal(0.0) result['reporting_period']['total_in_kgco2e_saving'] = Decimal(0.0) result['reporting_period']['increment_rate_in_kgce_saving'] = Decimal(0.0) result['reporting_period']['increment_rate_in_kgco2e_saving'] = Decimal(0.0) if energy_category_set is not None and len(energy_category_set) > 0: for energy_category_id in energy_category_set: result['reporting_period']['names'].append(energy_category_dict[energy_category_id]['name']) result['reporting_period']['energy_category_ids'].append(energy_category_id) result['reporting_period']['units'].append(energy_category_dict[energy_category_id]['unit_of_measure']) result['reporting_period']['timestamps'].append(reporting[energy_category_id]['timestamps']) result['reporting_period']['values_saving'].append(reporting[energy_category_id]['values_saving']) result['reporting_period']['subtotals_saving'].append(reporting[energy_category_id]['subtotal_saving']) result['reporting_period']['subtotals_in_kgce_saving'].append( reporting[energy_category_id]['subtotal_in_kgce_saving']) result['reporting_period']['subtotals_in_kgco2e_saving'].append( reporting[energy_category_id]['subtotal_in_kgco2e_saving']) result['reporting_period']['subtotals_per_unit_area_saving'].append( reporting[energy_category_id]['subtotal_saving'] / shopfloor['area'] if shopfloor['area'] > 0.0 else None) result['reporting_period']['increment_rates_saving'].append( (reporting[energy_category_id]['subtotal_saving'] - base[energy_category_id]['subtotal_saving']) / base[energy_category_id]['subtotal_saving'] if base[energy_category_id]['subtotal_saving'] > 0.0 else None) result['reporting_period']['total_in_kgce_saving'] += \ reporting[energy_category_id]['subtotal_in_kgce_saving'] result['reporting_period']['total_in_kgco2e_saving'] += \ reporting[energy_category_id]['subtotal_in_kgco2e_saving'] result['reporting_period']['total_in_kgco2e_per_unit_area_saving'] = \ result['reporting_period']['total_in_kgce_saving'] / shopfloor['area'] if shopfloor['area'] > 0.0 else None result['reporting_period']['increment_rate_in_kgce_saving'] = \ (result['reporting_period']['total_in_kgce_saving'] - result['base_period']['total_in_kgce_saving']) / \ result['base_period']['total_in_kgce_saving'] \ if result['base_period']['total_in_kgce_saving'] > Decimal(0.0) else None result['reporting_period']['total_in_kgce_per_unit_area_saving'] = \ result['reporting_period']['total_in_kgco2e_saving'] / shopfloor['area'] \ if shopfloor['area'] > 0.0 else None result['reporting_period']['increment_rate_in_kgco2e_saving'] = \ (result['reporting_period']['total_in_kgco2e_saving'] - result['base_period']['total_in_kgco2e_saving']) / \ result['base_period']['total_in_kgco2e_saving'] \ if result['base_period']['total_in_kgco2e_saving'] > Decimal(0.0) else None result['parameters'] = { "names": parameters_data['names'], "timestamps": parameters_data['timestamps'], "values": parameters_data['values'] } resp.body = json.dumps(result)
def on_get(req, resp): print(req.params) combined_equipment_id = req.params.get('combinedequipmentid') combined_equipment_uuid = req.params.get('combinedequipmentuuid') period_type = req.params.get('periodtype') base_start_datetime_local = req.params.get('baseperiodstartdatetime') base_end_datetime_local = req.params.get('baseperiodenddatetime') reporting_start_datetime_local = req.params.get( 'reportingperiodstartdatetime') reporting_end_datetime_local = req.params.get( 'reportingperiodenddatetime') ################################################################################################################ # Step 1: valid parameters ################################################################################################################ if combined_equipment_id is None and combined_equipment_uuid is None: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_COMBINED_EQUIPMENT_ID') if combined_equipment_id is not None: combined_equipment_id = str.strip(combined_equipment_id) if not combined_equipment_id.isdigit() or int( combined_equipment_id) <= 0: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_COMBINED_EQUIPMENT_ID') if combined_equipment_uuid is not None: regex = re.compile( '^[a-f0-9]{8}-?[a-f0-9]{4}-?4[a-f0-9]{3}-?[89ab][a-f0-9]{3}-?[a-f0-9]{12}\Z', re.I) match = regex.match(str.strip(combined_equipment_uuid)) if not bool(match): raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_COMBINED_EQUIPMENT_UUID') if period_type is None: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_PERIOD_TYPE') else: period_type = str.strip(period_type) if period_type not in [ 'hourly', 'daily', 'weekly', 'monthly', 'yearly' ]: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_PERIOD_TYPE') timezone_offset = int(config.utc_offset[1:3]) * 60 + int( config.utc_offset[4:6]) if config.utc_offset[0] == '-': timezone_offset = -timezone_offset base_start_datetime_utc = None if base_start_datetime_local is not None and len( str.strip(base_start_datetime_local)) > 0: base_start_datetime_local = str.strip(base_start_datetime_local) try: base_start_datetime_utc = datetime.strptime(base_start_datetime_local, '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ timedelta(minutes=timezone_offset) except ValueError: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_BASE_PERIOD_START_DATETIME") base_end_datetime_utc = None if base_end_datetime_local is not None and len( str.strip(base_end_datetime_local)) > 0: base_end_datetime_local = str.strip(base_end_datetime_local) try: base_end_datetime_utc = datetime.strptime(base_end_datetime_local, '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ timedelta(minutes=timezone_offset) except ValueError: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_BASE_PERIOD_END_DATETIME") if base_start_datetime_utc is not None and base_end_datetime_utc is not None and \ base_start_datetime_utc >= base_end_datetime_utc: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_BASE_PERIOD_END_DATETIME') if reporting_start_datetime_local is None: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_REPORTING_PERIOD_START_DATETIME") else: reporting_start_datetime_local = str.strip( reporting_start_datetime_local) try: reporting_start_datetime_utc = datetime.strptime(reporting_start_datetime_local, '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ timedelta(minutes=timezone_offset) except ValueError: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_REPORTING_PERIOD_START_DATETIME") if reporting_end_datetime_local is None: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_REPORTING_PERIOD_END_DATETIME") else: reporting_end_datetime_local = str.strip( reporting_end_datetime_local) try: reporting_end_datetime_utc = datetime.strptime(reporting_end_datetime_local, '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ timedelta(minutes=timezone_offset) except ValueError: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_REPORTING_PERIOD_END_DATETIME") if reporting_start_datetime_utc >= reporting_end_datetime_utc: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_REPORTING_PERIOD_END_DATETIME') ################################################################################################################ # Step 2: query the combined equipment ################################################################################################################ cnx_system = mysql.connector.connect(**config.myems_system_db) cursor_system = cnx_system.cursor() cnx_energy = mysql.connector.connect(**config.myems_energy_db) cursor_energy = cnx_energy.cursor() cnx_historical = mysql.connector.connect(**config.myems_historical_db) cursor_historical = cnx_historical.cursor() if combined_equipment_id is not None: cursor_system.execute( " SELECT id, name, cost_center_id " " FROM tbl_combined_equipments " " WHERE id = %s ", (combined_equipment_id, )) row_combined_equipment = cursor_system.fetchone() elif combined_equipment_uuid is not None: cursor_system.execute( " SELECT id, name, cost_center_id " " FROM tbl_combined_equipments " " WHERE uuid = %s ", (combined_equipment_uuid, )) row_combined_equipment = cursor_system.fetchone() if row_combined_equipment is None: if cursor_system: cursor_system.close() if cnx_system: cnx_system.close() if cursor_energy: cursor_energy.close() if cnx_energy: cnx_energy.close() if cursor_historical: cursor_historical.close() if cnx_historical: cnx_historical.close() raise falcon.HTTPError( falcon.HTTP_404, title='API.NOT_FOUND', description='API.COMBINED_EQUIPMENT_NOT_FOUND') combined_equipment = dict() combined_equipment['id'] = row_combined_equipment[0] combined_equipment['name'] = row_combined_equipment[1] combined_equipment['cost_center_id'] = row_combined_equipment[2] ################################################################################################################ # Step 3: query energy categories ################################################################################################################ energy_category_set = set() # query energy categories in base period cursor_energy.execute( " SELECT DISTINCT(energy_category_id) " " FROM tbl_combined_equipment_input_category_hourly " " WHERE combined_equipment_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s ", (combined_equipment['id'], base_start_datetime_utc, base_end_datetime_utc)) rows_energy_categories = cursor_energy.fetchall() if rows_energy_categories is not None or len( rows_energy_categories) > 0: for row_energy_category in rows_energy_categories: energy_category_set.add(row_energy_category[0]) # query energy categories in reporting period cursor_energy.execute( " SELECT DISTINCT(energy_category_id) " " FROM tbl_combined_equipment_input_category_hourly " " WHERE combined_equipment_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s ", (combined_equipment['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) rows_energy_categories = cursor_energy.fetchall() if rows_energy_categories is not None or len( rows_energy_categories) > 0: for row_energy_category in rows_energy_categories: energy_category_set.add(row_energy_category[0]) # query all energy categories in base period and reporting period cursor_system.execute( " SELECT id, name, unit_of_measure, kgce, kgco2e " " FROM tbl_energy_categories " " ORDER BY id ", ) rows_energy_categories = cursor_system.fetchall() if rows_energy_categories is None or len(rows_energy_categories) == 0: if cursor_system: cursor_system.close() if cnx_system: cnx_system.close() if cursor_energy: cursor_energy.close() if cnx_energy: cnx_energy.close() if cursor_historical: cursor_historical.close() if cnx_historical: cnx_historical.close() raise falcon.HTTPError(falcon.HTTP_404, title='API.NOT_FOUND', description='API.ENERGY_CATEGORY_NOT_FOUND') energy_category_dict = dict() for row_energy_category in rows_energy_categories: if row_energy_category[0] in energy_category_set: energy_category_dict[row_energy_category[0]] = { "name": row_energy_category[1], "unit_of_measure": row_energy_category[2], "kgce": row_energy_category[3], "kgco2e": row_energy_category[4] } ################################################################################################################ # Step 4: query associated points ################################################################################################################ point_list = list() cursor_system.execute( " SELECT p.id, ep.name, p.units, p.object_type " " FROM tbl_combined_equipments e, tbl_combined_equipments_parameters ep, tbl_points p " " WHERE e.id = %s AND e.id = ep.combined_equipment_id AND ep.parameter_type = 'point' " " AND ep.point_id = p.id " " ORDER BY p.id ", (combined_equipment['id'], )) rows_points = cursor_system.fetchall() if rows_points is not None and len(rows_points) > 0: for row in rows_points: point_list.append({ "id": row[0], "name": row[1], "units": row[2], "object_type": row[3] }) ################################################################################################################ # Step 5: query associated equipments ################################################################################################################ associated_equipment_list = list() cursor_system.execute( " SELECT e.id, e.name " " FROM tbl_equipments e,tbl_combined_equipments_equipments ee" " WHERE ee.combined_equipment_id = %s AND e.id = ee.equipment_id" " ORDER BY id ", (combined_equipment['id'], )) rows_associated_equipments = cursor_system.fetchall() if rows_associated_equipments is not None and len( rows_associated_equipments) > 0: for row in rows_associated_equipments: associated_equipment_list.append({ "id": row[0], "name": row[1] }) ################################################################################################################ # Step 6: query base period energy input ################################################################################################################ base = dict() if energy_category_set is not None and len(energy_category_set) > 0: for energy_category_id in energy_category_set: base[energy_category_id] = dict() base[energy_category_id]['timestamps'] = list() base[energy_category_id]['sub_averages'] = list() base[energy_category_id]['sub_maximums'] = list() base[energy_category_id]['average'] = None base[energy_category_id]['maximum'] = None base[energy_category_id]['factor'] = None cursor_energy.execute( " SELECT start_datetime_utc, actual_value " " FROM tbl_combined_equipment_input_category_hourly " " WHERE combined_equipment_id = %s " " AND energy_category_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s " " ORDER BY start_datetime_utc ", (combined_equipment['id'], energy_category_id, base_start_datetime_utc, base_end_datetime_utc)) rows_combined_equipment_hourly = cursor_energy.fetchall() rows_combined_equipment_periodically, \ base[energy_category_id]['average'], \ base[energy_category_id]['maximum'] = \ utilities.averaging_hourly_data_by_period(rows_combined_equipment_hourly, base_start_datetime_utc, base_end_datetime_utc, period_type) base[energy_category_id]['factor'] = \ (base[energy_category_id]['average'] / base[energy_category_id]['maximum'] if (base[energy_category_id]['average'] is not None and base[energy_category_id]['maximum'] is not None and base[energy_category_id]['maximum'] > Decimal(0.0)) else None) for row_combined_equipment_periodically in rows_combined_equipment_periodically: current_datetime_local = row_combined_equipment_periodically[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) if period_type == 'hourly': current_datetime = current_datetime_local.strftime( '%Y-%m-%dT%H:%M:%S') elif period_type == 'daily': current_datetime = current_datetime_local.strftime( '%Y-%m-%d') elif period_type == 'weekly': current_datetime = current_datetime_local.strftime( '%Y-%m-%d') elif period_type == 'monthly': current_datetime = current_datetime_local.strftime( '%Y-%m') elif period_type == 'yearly': current_datetime = current_datetime_local.strftime( '%Y') base[energy_category_id]['timestamps'].append( current_datetime) base[energy_category_id]['sub_averages'].append( row_combined_equipment_periodically[1]) base[energy_category_id]['sub_maximums'].append( row_combined_equipment_periodically[2]) ################################################################################################################ # Step 7: query reporting period energy input ################################################################################################################ reporting = dict() if energy_category_set is not None and len(energy_category_set) > 0: for energy_category_id in energy_category_set: reporting[energy_category_id] = dict() reporting[energy_category_id]['timestamps'] = list() reporting[energy_category_id]['sub_averages'] = list() reporting[energy_category_id]['sub_maximums'] = list() reporting[energy_category_id]['average'] = None reporting[energy_category_id]['maximum'] = None reporting[energy_category_id]['factor'] = None cursor_energy.execute( " SELECT start_datetime_utc, actual_value " " FROM tbl_combined_equipment_input_category_hourly " " WHERE combined_equipment_id = %s " " AND energy_category_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s " " ORDER BY start_datetime_utc ", (combined_equipment['id'], energy_category_id, reporting_start_datetime_utc, reporting_end_datetime_utc)) rows_combined_equipment_hourly = cursor_energy.fetchall() rows_combined_equipment_periodically, \ reporting[energy_category_id]['average'], \ reporting[energy_category_id]['maximum'] = \ utilities.averaging_hourly_data_by_period(rows_combined_equipment_hourly, reporting_start_datetime_utc, reporting_end_datetime_utc, period_type) reporting[energy_category_id]['factor'] = \ (reporting[energy_category_id]['average'] / reporting[energy_category_id]['maximum'] if (reporting[energy_category_id]['average'] is not None and reporting[energy_category_id]['maximum'] is not None and reporting[energy_category_id]['maximum'] > Decimal(0.0)) else None) for row_combined_equipment_periodically in rows_combined_equipment_periodically: current_datetime_local = row_combined_equipment_periodically[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) if period_type == 'hourly': current_datetime = current_datetime_local.strftime( '%Y-%m-%dT%H:%M:%S') elif period_type == 'daily': current_datetime = current_datetime_local.strftime( '%Y-%m-%d') elif period_type == 'weekly': current_datetime = current_datetime_local.strftime( '%Y-%m-%d') elif period_type == 'monthly': current_datetime = current_datetime_local.strftime( '%Y-%m') elif period_type == 'yearly': current_datetime = current_datetime_local.strftime( '%Y') reporting[energy_category_id]['timestamps'].append( current_datetime) reporting[energy_category_id]['sub_averages'].append( row_combined_equipment_periodically[1]) reporting[energy_category_id]['sub_maximums'].append( row_combined_equipment_periodically[2]) ################################################################################################################ # Step 8: query tariff data ################################################################################################################ parameters_data = dict() parameters_data['names'] = list() parameters_data['timestamps'] = list() parameters_data['values'] = list() if energy_category_set is not None and len(energy_category_set) > 0: for energy_category_id in energy_category_set: energy_category_tariff_dict = \ utilities.get_energy_category_tariffs(combined_equipment['cost_center_id'], energy_category_id, reporting_start_datetime_utc, reporting_end_datetime_utc) tariff_timestamp_list = list() tariff_value_list = list() for k, v in energy_category_tariff_dict.items(): # convert k from utc to local k = k + timedelta(minutes=timezone_offset) tariff_timestamp_list.append(k.isoformat()[0:19][0:19]) tariff_value_list.append(v) parameters_data['names'].append( 'TARIFF-' + energy_category_dict[energy_category_id]['name']) parameters_data['timestamps'].append(tariff_timestamp_list) parameters_data['values'].append(tariff_value_list) ################################################################################################################ # Step 9: query associated points data ################################################################################################################ for point in point_list: point_values = [] point_timestamps = [] if point['object_type'] == 'ANALOG_VALUE': query = (" SELECT utc_date_time, actual_value " " FROM tbl_analog_value " " WHERE point_id = %s " " AND utc_date_time BETWEEN %s AND %s " " ORDER BY utc_date_time ") cursor_historical.execute( query, (point['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) rows = cursor_historical.fetchall() if rows is not None and len(rows) > 0: for row in rows: current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) current_datetime = current_datetime_local.strftime( '%Y-%m-%dT%H:%M:%S') point_timestamps.append(current_datetime) point_values.append(row[1]) elif point['object_type'] == 'ENERGY_VALUE': query = (" SELECT utc_date_time, actual_value " " FROM tbl_energy_value " " WHERE point_id = %s " " AND utc_date_time BETWEEN %s AND %s " " ORDER BY utc_date_time ") cursor_historical.execute( query, (point['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) rows = cursor_historical.fetchall() if rows is not None and len(rows) > 0: for row in rows: current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) current_datetime = current_datetime_local.strftime( '%Y-%m-%dT%H:%M:%S') point_timestamps.append(current_datetime) point_values.append(row[1]) elif point['object_type'] == 'DIGITAL_VALUE': query = (" SELECT utc_date_time, actual_value " " FROM tbl_digital_value " " WHERE point_id = %s " " AND utc_date_time BETWEEN %s AND %s " " ORDER BY utc_date_time ") cursor_historical.execute( query, (point['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) rows = cursor_historical.fetchall() if rows is not None and len(rows) > 0: for row in rows: current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) current_datetime = current_datetime_local.strftime( '%Y-%m-%dT%H:%M:%S') point_timestamps.append(current_datetime) point_values.append(row[1]) parameters_data['names'].append(point['name'] + ' (' + point['units'] + ')') parameters_data['timestamps'].append(point_timestamps) parameters_data['values'].append(point_values) ################################################################################################################ # Step 10: query associated equipments energy input ################################################################################################################ associated_equipment_data = dict() if energy_category_set is not None and len(energy_category_set) > 0: for energy_category_id in energy_category_set: associated_equipment_data[energy_category_id] = dict() associated_equipment_data[energy_category_id][ 'associated_equipment_names'] = list() associated_equipment_data[energy_category_id][ 'average'] = list() associated_equipment_data[energy_category_id][ 'maximum'] = list() associated_equipment_data[energy_category_id][ 'sub_averages'] = list() associated_equipment_data[energy_category_id][ 'sub_maximums'] = list() for associated_equipment in associated_equipment_list: associated_equipment_data[energy_category_id][ 'associated_equipment_names'].append( associated_equipment['name']) cursor_energy.execute( " SELECT start_datetime_utc, actual_value " " FROM tbl_equipment_input_category_hourly " " WHERE equipment_id = %s " " AND energy_category_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s " " ORDER BY start_datetime_utc ", (associated_equipment['id'], energy_category_id, reporting_start_datetime_utc, reporting_end_datetime_utc)) rows_associated_equipments_hourly = cursor_energy.fetchall( ) rows_associated_equipment_periodically, \ associated_equipment_data[energy_category_id]['average'], \ associated_equipment_data[energy_category_id]['maximum'] = \ utilities.averaging_hourly_data_by_period(rows_associated_equipments_hourly, reporting_start_datetime_utc, reporting_end_datetime_utc, period_type) associated_equipment_data[energy_category_id][ 'sub_averages'].append( associated_equipment_data[energy_category_id] ['average']) associated_equipment_data[energy_category_id][ 'sub_maximums'].append( associated_equipment_data[energy_category_id] ['maximum']) ################################################################################################################ # Step 11: construct the report ################################################################################################################ if cursor_system: cursor_system.close() if cnx_system: cnx_system.close() if cursor_energy: cursor_energy.close() if cnx_energy: cnx_energy.close() if cursor_historical: cursor_historical.close() if cnx_historical: cnx_historical.close() result = dict() result['combined_equipment'] = dict() result['combined_equipment']['name'] = combined_equipment['name'] result['base_period'] = dict() result['base_period']['names'] = list() result['base_period']['units'] = list() result['base_period']['timestamps'] = list() result['base_period']['sub_averages'] = list() result['base_period']['sub_maximums'] = list() result['base_period']['averages'] = list() result['base_period']['maximums'] = list() result['base_period']['factors'] = list() if energy_category_set is not None and len(energy_category_set) > 0: for energy_category_id in energy_category_set: result['base_period']['names'].append( energy_category_dict[energy_category_id]['name']) result['base_period']['units'].append( energy_category_dict[energy_category_id] ['unit_of_measure']) result['base_period']['timestamps'].append( base[energy_category_id]['timestamps']) result['base_period']['sub_averages'].append( base[energy_category_id]['sub_averages']) result['base_period']['sub_maximums'].append( base[energy_category_id]['sub_maximums']) result['base_period']['averages'].append( base[energy_category_id]['average']) result['base_period']['maximums'].append( base[energy_category_id]['maximum']) result['base_period']['factors'].append( base[energy_category_id]['factor']) result['reporting_period'] = dict() result['reporting_period']['names'] = list() result['reporting_period']['energy_category_ids'] = list() result['reporting_period']['units'] = list() result['reporting_period']['timestamps'] = list() result['reporting_period']['sub_averages'] = list() result['reporting_period']['sub_maximums'] = list() result['reporting_period']['averages'] = list() result['reporting_period']['averages_increment_rate'] = list() result['reporting_period']['maximums'] = list() result['reporting_period']['maximums_increment_rate'] = list() result['reporting_period']['factors'] = list() result['reporting_period']['factors_increment_rate'] = list() if energy_category_set is not None and len(energy_category_set) > 0: for energy_category_id in energy_category_set: result['reporting_period']['names'].append( energy_category_dict[energy_category_id]['name']) result['reporting_period']['energy_category_ids'].append( energy_category_id) result['reporting_period']['units'].append( energy_category_dict[energy_category_id] ['unit_of_measure']) result['reporting_period']['timestamps'].append( reporting[energy_category_id]['timestamps']) result['reporting_period']['sub_averages'].append( reporting[energy_category_id]['sub_averages']) result['reporting_period']['sub_maximums'].append( reporting[energy_category_id]['sub_maximums']) result['reporting_period']['averages'].append( reporting[energy_category_id]['average']) result['reporting_period']['averages_increment_rate'].append( (reporting[energy_category_id]['average'] - base[energy_category_id]['average']) / base[energy_category_id]['average'] if ( reporting[energy_category_id]['average'] is not None and base[energy_category_id]['average'] is not None and base[energy_category_id]['average'] > Decimal(0.0) ) else None) result['reporting_period']['maximums'].append( reporting[energy_category_id]['maximum']) result['reporting_period']['maximums_increment_rate'].append( (reporting[energy_category_id]['maximum'] - base[energy_category_id]['maximum']) / base[energy_category_id]['maximum'] if ( reporting[energy_category_id]['maximum'] is not None and base[energy_category_id]['maximum'] is not None and base[energy_category_id]['maximum'] > Decimal(0.0) ) else None) result['reporting_period']['factors'].append( reporting[energy_category_id]['factor']) result['reporting_period']['factors_increment_rate'].append( (reporting[energy_category_id]['factor'] - base[energy_category_id]['factor']) / base[energy_category_id]['factor'] if ( reporting[energy_category_id]['factor'] is not None and base[energy_category_id]['factor'] is not None and base[energy_category_id]['factor'] > Decimal(0.0) ) else None) result['parameters'] = { "names": parameters_data['names'], "timestamps": parameters_data['timestamps'], "values": parameters_data['values'] } result['associated_equipment'] = dict() result['associated_equipment']['energy_category_names'] = list() result['associated_equipment']['units'] = list() result['associated_equipment'][ 'associated_equipment_names_array'] = list() result['associated_equipment']['sub_averages_array'] = list() result['associated_equipment']['sub_maximums_array'] = list() if energy_category_set is not None and len(energy_category_set) > 0: for energy_category_id in energy_category_set: result['associated_equipment']['energy_category_names'].append( energy_category_dict[energy_category_id]['name']) result['associated_equipment']['units'].append( energy_category_dict[energy_category_id] ['unit_of_measure']) result['associated_equipment'][ 'associated_equipment_names_array'].append( associated_equipment_data[energy_category_id] ['associated_equipment_names']) result['associated_equipment']['sub_averages_array'].append( associated_equipment_data[energy_category_id] ['sub_averages']) result['associated_equipment']['sub_maximums_array'].append( associated_equipment_data[energy_category_id] ['sub_maximums']) # export result to Excel file and then encode the file to base64 string result[ 'excel_bytes_base64'] = excelexporters.combinedequipmentload.export( result, combined_equipment['name'], reporting_start_datetime_local, reporting_end_datetime_local, period_type) resp.text = json.dumps(result)
def on_get(req, resp): print(req.params) tenant_id = req.params.get('tenantid') reporting_start_datetime_local = req.params.get( 'reportingperiodstartdatetime') reporting_end_datetime_local = req.params.get( 'reportingperiodenddatetime') period_type = 'daily' ################################################################################################################ # Step 1: valid parameters ################################################################################################################ if tenant_id is None: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_TENANT_ID') else: tenant_id = str.strip(tenant_id) if not tenant_id.isdigit() or int(tenant_id) <= 0: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_TENANT_ID') timezone_offset = int(config.utc_offset[1:3]) * 60 + int( config.utc_offset[4:6]) if config.utc_offset[0] == '-': timezone_offset = -timezone_offset if reporting_start_datetime_local is None: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_REPORTING_PERIOD_BEGINS_DATETIME") else: reporting_start_datetime_local = str.strip( reporting_start_datetime_local) try: reporting_start_datetime_utc = datetime.strptime(reporting_start_datetime_local, '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ timedelta(minutes=timezone_offset) except ValueError: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_REPORTING_PERIOD_BEGINS_DATETIME") if reporting_end_datetime_local is None: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_REPORTING_PERIOD_ENDS_DATETIME") else: reporting_end_datetime_local = str.strip( reporting_end_datetime_local) try: reporting_end_datetime_utc = datetime.strptime(reporting_end_datetime_local, '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ timedelta(minutes=timezone_offset) except ValueError: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_REPORTING_PERIOD_ENDS_DATETIME") if reporting_start_datetime_utc >= reporting_end_datetime_utc: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_REPORTING_PERIOD_ENDS_DATETIME') ################################################################################################################ # Step 2: query the tenant ################################################################################################################ cnx_system = mysql.connector.connect(**config.myems_system_db) cursor_system = cnx_system.cursor() cnx_energy = mysql.connector.connect(**config.myems_energy_db) cursor_energy = cnx_energy.cursor() cnx_billing = mysql.connector.connect(**config.myems_billing_db) cursor_billing = cnx_billing.cursor() cursor_system.execute( " SELECT t.id, t.name, t.buildings, t.floors, t.rooms, t.lease_number, " " c.email, c.phone, cost_center_id " " FROM tbl_tenants t, tbl_contacts c " " WHERE t.id = %s AND t.contact_id = c.id ", (tenant_id, )) row_tenant = cursor_system.fetchone() if row_tenant is None: if cursor_system: cursor_system.close() if cnx_system: cnx_system.disconnect() if cursor_energy: cursor_energy.close() if cnx_energy: cnx_energy.disconnect() if cursor_billing: cursor_billing.close() if cnx_billing: cnx_billing.disconnect() raise falcon.HTTPError(falcon.HTTP_404, title='API.NOT_FOUND', description='API.TENANT_NOT_FOUND') tenant = dict() tenant['id'] = row_tenant[0] tenant['name'] = row_tenant[1] tenant['buildings'] = row_tenant[2] tenant['floors'] = row_tenant[3] tenant['rooms'] = row_tenant[4] tenant['lease_number'] = row_tenant[5] tenant['email'] = row_tenant[6] tenant['phone'] = row_tenant[7] tenant['cost_center_id'] = row_tenant[8] ################################################################################################################ # Step 3: query energy categories ################################################################################################################ energy_category_set = set() # query energy categories in reporting period cursor_billing.execute( " SELECT DISTINCT(energy_category_id) " " FROM tbl_tenant_input_category_hourly " " WHERE tenant_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s ", (tenant['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) rows_energy_categories = cursor_billing.fetchall() if rows_energy_categories is not None or len( rows_energy_categories) > 0: for row_energy_category in rows_energy_categories: energy_category_set.add(row_energy_category[0]) # query all energy categories cursor_system.execute( " SELECT id, name, unit_of_measure, kgce, kgco2e " " FROM tbl_energy_categories " " ORDER BY id ", ) rows_energy_categories = cursor_system.fetchall() if rows_energy_categories is None or len(rows_energy_categories) == 0: if cursor_system: cursor_system.close() if cnx_system: cnx_system.disconnect() if cursor_energy: cursor_energy.close() if cnx_energy: cnx_energy.disconnect() if cursor_billing: cursor_billing.close() if cnx_billing: cnx_billing.disconnect() raise falcon.HTTPError(falcon.HTTP_404, title='API.NOT_FOUND', description='API.ENERGY_CATEGORY_NOT_FOUND') energy_category_dict = dict() for row_energy_category in rows_energy_categories: if row_energy_category[0] in energy_category_set: energy_category_dict[row_energy_category[0]] = { "name": row_energy_category[1], "unit_of_measure": row_energy_category[2], "kgce": row_energy_category[3], "kgco2e": row_energy_category[4] } ################################################################################################################ # Step 4: query reporting period energy input ################################################################################################################ reporting_input = dict() if energy_category_set is not None and len(energy_category_set) > 0: for energy_category_id in energy_category_set: reporting_input[energy_category_id] = dict() reporting_input[energy_category_id]['timestamps'] = list() reporting_input[energy_category_id]['values'] = list() reporting_input[energy_category_id]['subtotal'] = Decimal(0.0) cursor_energy.execute( " SELECT start_datetime_utc, actual_value " " FROM tbl_tenant_input_category_hourly " " WHERE tenant_id = %s " " AND energy_category_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s " " ORDER BY start_datetime_utc ", (tenant['id'], energy_category_id, reporting_start_datetime_utc, reporting_end_datetime_utc)) rows_tenant_hourly = cursor_energy.fetchall() rows_tenant_periodically = utilities.aggregate_hourly_data_by_period( rows_tenant_hourly, reporting_start_datetime_utc, reporting_end_datetime_utc, period_type) for row_tenant_periodically in rows_tenant_periodically: current_datetime_local = row_tenant_periodically[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) if period_type == 'hourly': current_datetime = current_datetime_local.strftime( '%Y-%m-%dT%H:%M:%S') elif period_type == 'daily': current_datetime = current_datetime_local.strftime( '%Y-%m-%d') elif period_type == 'monthly': current_datetime = current_datetime_local.strftime( '%Y-%m') elif period_type == 'yearly': current_datetime = current_datetime_local.strftime( '%Y') actual_value = Decimal(0.0) if row_tenant_periodically[ 1] is None else row_tenant_periodically[1] reporting_input[energy_category_id]['timestamps'].append( current_datetime) reporting_input[energy_category_id]['values'].append( actual_value) reporting_input[energy_category_id][ 'subtotal'] += actual_value ################################################################################################################ # Step 5: query reporting period energy cost ################################################################################################################ reporting_cost = dict() if energy_category_set is not None and len(energy_category_set) > 0: for energy_category_id in energy_category_set: reporting_cost[energy_category_id] = dict() reporting_cost[energy_category_id]['timestamps'] = list() reporting_cost[energy_category_id]['values'] = list() reporting_cost[energy_category_id]['subtotal'] = Decimal(0.0) cursor_billing.execute( " SELECT start_datetime_utc, actual_value " " FROM tbl_tenant_input_category_hourly " " WHERE tenant_id = %s " " AND energy_category_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s " " ORDER BY start_datetime_utc ", (tenant['id'], energy_category_id, reporting_start_datetime_utc, reporting_end_datetime_utc)) rows_tenant_hourly = cursor_billing.fetchall() rows_tenant_periodically = utilities.aggregate_hourly_data_by_period( rows_tenant_hourly, reporting_start_datetime_utc, reporting_end_datetime_utc, period_type) for row_tenant_periodically in rows_tenant_periodically: current_datetime_local = row_tenant_periodically[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) if period_type == 'hourly': current_datetime = current_datetime_local.strftime( '%Y-%m-%dT%H:%M:%S') elif period_type == 'daily': current_datetime = current_datetime_local.strftime( '%Y-%m-%d') elif period_type == 'monthly': current_datetime = current_datetime_local.strftime( '%Y-%m') elif period_type == 'yearly': current_datetime = current_datetime_local.strftime( '%Y') actual_value = Decimal(0.0) if row_tenant_periodically[ 1] is None else row_tenant_periodically[1] reporting_cost[energy_category_id]['timestamps'].append( current_datetime) reporting_cost[energy_category_id]['values'].append( actual_value) reporting_cost[energy_category_id][ 'subtotal'] += actual_value ################################################################################################################ # Step 6: query tariff data ################################################################################################################ parameters_data = dict() parameters_data['names'] = list() parameters_data['timestamps'] = list() parameters_data['values'] = list() if energy_category_set is not None and len(energy_category_set) > 0: for energy_category_id in energy_category_set: energy_category_tariff_dict = utilities.get_energy_category_tariffs( tenant['cost_center_id'], energy_category_id, reporting_start_datetime_utc, reporting_end_datetime_utc) tariff_timestamp_list = list() tariff_value_list = list() for k, v in energy_category_tariff_dict.items(): # convert k from utc to local k = k + timedelta(minutes=timezone_offset) tariff_timestamp_list.append(k.isoformat()[0:19][0:19]) tariff_value_list.append(v) parameters_data['names'].append( 'TARIFF-' + energy_category_dict[energy_category_id]['name']) parameters_data['timestamps'].append(tariff_timestamp_list) parameters_data['values'].append(tariff_value_list) ################################################################################################################ # Step 7: construct the report ################################################################################################################ if cursor_system: cursor_system.close() if cnx_system: cnx_system.disconnect() if cursor_energy: cursor_energy.close() if cnx_energy: cnx_energy.disconnect() if cursor_billing: cursor_billing.close() if cnx_billing: cnx_billing.disconnect() result = dict() result['tenant'] = dict() result['tenant']['name'] = tenant['name'] result['tenant']['buildings'] = tenant['buildings'] result['tenant']['floors'] = tenant['floors'] result['tenant']['rooms'] = tenant['rooms'] result['tenant']['lease_number'] = tenant['lease_number'] result['tenant']['email'] = tenant['email'] result['tenant']['phone'] = tenant['phone'] result['reporting_period'] = dict() result['reporting_period']['names'] = list() result['reporting_period']['energy_category_ids'] = list() result['reporting_period']['units'] = list() result['reporting_period']['subtotals_input'] = list() result['reporting_period']['subtotals_cost'] = list() result['reporting_period']['total_cost'] = Decimal(0.0) result['reporting_period']['currency_unit'] = config.currency_unit if energy_category_set is not None and len(energy_category_set) > 0: for energy_category_id in energy_category_set: result['reporting_period']['names'].append( energy_category_dict[energy_category_id]['name']) result['reporting_period']['energy_category_ids'].append( energy_category_id) result['reporting_period']['units'].append( energy_category_dict[energy_category_id] ['unit_of_measure']) result['reporting_period']['subtotals_input'].append( reporting_input[energy_category_id]['subtotal']) result['reporting_period']['subtotals_cost'].append( reporting_cost[energy_category_id]['subtotal']) result['reporting_period']['total_cost'] += reporting_cost[ energy_category_id]['subtotal'] result['parameters'] = { "names": parameters_data['names'], "timestamps": parameters_data['timestamps'], "values": parameters_data['values'] } resp.body = json.dumps(result)
def on_get(req, resp): print(req.params) tenant_id = req.params.get('tenantid') period_type = req.params.get('periodtype') base_start_datetime_local = req.params.get('baseperiodstartdatetime') base_end_datetime_local = req.params.get('baseperiodenddatetime') reporting_start_datetime_local = req.params.get('reportingperiodstartdatetime') reporting_end_datetime_local = req.params.get('reportingperiodenddatetime') ################################################################################################################ # Step 1: valid parameters ################################################################################################################ if tenant_id is None: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_TENANT_ID') else: tenant_id = str.strip(tenant_id) if not tenant_id.isdigit() or int(tenant_id) <= 0: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_TENANT_ID') if period_type is None: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_PERIOD_TYPE') else: period_type = str.strip(period_type) if period_type not in ['hourly', 'daily', 'monthly', 'yearly']: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_PERIOD_TYPE') timezone_offset = int(config.utc_offset[1:3]) * 60 + int(config.utc_offset[4:6]) if config.utc_offset[0] == '-': timezone_offset = -timezone_offset base_start_datetime_utc = None if base_start_datetime_local is not None and len(str.strip(base_start_datetime_local)) > 0: base_start_datetime_local = str.strip(base_start_datetime_local) try: base_start_datetime_utc = datetime.strptime(base_start_datetime_local, '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ timedelta(minutes=timezone_offset) except ValueError: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_BASE_PERIOD_START_DATETIME") base_end_datetime_utc = None if base_end_datetime_local is not None and len(str.strip(base_end_datetime_local)) > 0: base_end_datetime_local = str.strip(base_end_datetime_local) try: base_end_datetime_utc = datetime.strptime(base_end_datetime_local, '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ timedelta(minutes=timezone_offset) except ValueError: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_BASE_PERIOD_END_DATETIME") if base_start_datetime_utc is not None and base_end_datetime_utc is not None and \ base_start_datetime_utc >= base_end_datetime_utc: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_BASE_PERIOD_END_DATETIME') if reporting_start_datetime_local is None: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_REPORTING_PERIOD_START_DATETIME") else: reporting_start_datetime_local = str.strip(reporting_start_datetime_local) try: reporting_start_datetime_utc = datetime.strptime(reporting_start_datetime_local, '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ timedelta(minutes=timezone_offset) except ValueError: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_REPORTING_PERIOD_START_DATETIME") if reporting_end_datetime_local is None: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_REPORTING_PERIOD_END_DATETIME") else: reporting_end_datetime_local = str.strip(reporting_end_datetime_local) try: reporting_end_datetime_utc = datetime.strptime(reporting_end_datetime_local, '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ timedelta(minutes=timezone_offset) except ValueError: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_REPORTING_PERIOD_END_DATETIME") if reporting_start_datetime_utc >= reporting_end_datetime_utc: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_REPORTING_PERIOD_END_DATETIME') ################################################################################################################ # Step 2: query the tenant ################################################################################################################ cnx_system = mysql.connector.connect(**config.myems_system_db) cursor_system = cnx_system.cursor() cnx_energy = mysql.connector.connect(**config.myems_energy_db) cursor_energy = cnx_energy.cursor() cnx_historical = mysql.connector.connect(**config.myems_historical_db) cursor_historical = cnx_historical.cursor() cursor_system.execute(" SELECT id, name, area, cost_center_id " " FROM tbl_tenants " " WHERE id = %s ", (tenant_id,)) row_tenant = cursor_system.fetchone() if row_tenant is None: if cursor_system: cursor_system.close() if cnx_system: cnx_system.disconnect() if cursor_energy: cursor_energy.close() if cnx_energy: cnx_energy.disconnect() if cnx_historical: cnx_historical.close() if cursor_historical: cursor_historical.disconnect() raise falcon.HTTPError(falcon.HTTP_404, title='API.NOT_FOUND', description='API.TENANT_NOT_FOUND') tenant = dict() tenant['id'] = row_tenant[0] tenant['name'] = row_tenant[1] tenant['area'] = row_tenant[2] tenant['cost_center_id'] = row_tenant[3] ################################################################################################################ # Step 3: query energy items ################################################################################################################ energy_item_set = set() # query energy items in base period cursor_energy.execute(" SELECT DISTINCT(energy_item_id) " " FROM tbl_tenant_input_item_hourly " " WHERE tenant_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s ", (tenant['id'], base_start_datetime_utc, base_end_datetime_utc)) rows_energy_items = cursor_energy.fetchall() if rows_energy_items is not None or len(rows_energy_items) > 0: for row_item in rows_energy_items: energy_item_set.add(row_item[0]) # query energy items in reporting period cursor_energy.execute(" SELECT DISTINCT(energy_item_id) " " FROM tbl_tenant_input_item_hourly " " WHERE tenant_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s ", (tenant['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) rows_energy_items = cursor_energy.fetchall() if rows_energy_items is not None or len(rows_energy_items) > 0: for row_item in rows_energy_items: energy_item_set.add(row_item[0]) # query all energy items in base period and reporting period cursor_system.execute(" SELECT ei.id, ei.name, ei.energy_category_id, " " ec.name AS energy_category_name, ec.unit_of_measure, ec.kgce, ec.kgco2e " " FROM tbl_energy_items ei, tbl_energy_categories ec " " WHERE ei.energy_category_id = ec.id " " ORDER BY ei.id ", ) rows_energy_items = cursor_system.fetchall() if rows_energy_items is None or len(rows_energy_items) == 0: if cursor_system: cursor_system.close() if cnx_system: cnx_system.disconnect() if cursor_energy: cursor_energy.close() if cnx_energy: cnx_energy.disconnect() if cnx_historical: cnx_historical.close() if cursor_historical: cursor_historical.disconnect() raise falcon.HTTPError(falcon.HTTP_404, title='API.NOT_FOUND', description='API.ENERGY_ITEM_NOT_FOUND') energy_item_dict = dict() for row_energy_item in rows_energy_items: if row_energy_item[0] in energy_item_set: energy_item_dict[row_energy_item[0]] = {"name": row_energy_item[1], "energy_category_id": row_energy_item[2], "energy_category_name": row_energy_item[3], "unit_of_measure": row_energy_item[4], "kgce": row_energy_item[5], "kgco2e": row_energy_item[6]} ################################################################################################################ # Step 4: query associated sensors ################################################################################################################ point_list = list() cursor_system.execute(" SELECT p.id, p.name, p.units, p.object_type " " FROM tbl_tenants t, tbl_sensors s, tbl_tenants_sensors ts, " " tbl_points p, tbl_sensors_points sp " " WHERE t.id = %s AND t.id = ts.tenant_id AND ts.sensor_id = s.id " " AND s.id = sp.sensor_id AND sp.point_id = p.id " " ORDER BY p.id ", (tenant['id'], )) rows_points = cursor_system.fetchall() if rows_points is not None and len(rows_points) > 0: for row in rows_points: point_list.append({"id": row[0], "name": row[1], "units": row[2], "object_type": row[3]}) ################################################################################################################ # Step 5: query associated points ################################################################################################################ cursor_system.execute(" SELECT po.id, po.name, po.units, po.object_type " " FROM tbl_tenants sp, tbl_tenants_points sppo, tbl_points po " " WHERE sp.id = %s AND sp.id = sppo.tenant_id AND sppo.point_id = po.id " " ORDER BY po.id ", (tenant['id'], )) rows_points = cursor_system.fetchall() if rows_points is not None and len(rows_points) > 0: for row in rows_points: point_list.append({"id": row[0], "name": row[1], "units": row[2], "object_type": row[3]}) ################################################################################################################ # Step 6: query base period energy input ################################################################################################################ base = dict() if energy_item_set is not None and len(energy_item_set) > 0: for energy_item_id in energy_item_set: base[energy_item_id] = dict() base[energy_item_id]['timestamps'] = list() base[energy_item_id]['values'] = list() base[energy_item_id]['subtotal'] = Decimal(0.0) cursor_energy.execute(" SELECT start_datetime_utc, actual_value " " FROM tbl_tenant_input_item_hourly " " WHERE tenant_id = %s " " AND energy_item_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s " " ORDER BY start_datetime_utc ", (tenant['id'], energy_item_id, base_start_datetime_utc, base_end_datetime_utc)) rows_tenant_hourly = cursor_energy.fetchall() rows_tenant_periodically = utilities.aggregate_hourly_data_by_period(rows_tenant_hourly, base_start_datetime_utc, base_end_datetime_utc, period_type) for row_tenant_periodically in rows_tenant_periodically: current_datetime_local = row_tenant_periodically[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) if period_type == 'hourly': current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') elif period_type == 'daily': current_datetime = current_datetime_local.strftime('%Y-%m-%d') elif period_type == 'monthly': current_datetime = current_datetime_local.strftime('%Y-%m') elif period_type == 'yearly': current_datetime = current_datetime_local.strftime('%Y') actual_value = Decimal(0.0) if row_tenant_periodically[1] is None else row_tenant_periodically[1] base[energy_item_id]['timestamps'].append(current_datetime) base[energy_item_id]['values'].append(actual_value) base[energy_item_id]['subtotal'] += actual_value ################################################################################################################ # Step 7: query reporting period energy input ################################################################################################################ reporting = dict() if energy_item_set is not None and len(energy_item_set) > 0: for energy_item_id in energy_item_set: reporting[energy_item_id] = dict() reporting[energy_item_id]['timestamps'] = list() reporting[energy_item_id]['values'] = list() reporting[energy_item_id]['subtotal'] = Decimal(0.0) reporting[energy_item_id]['toppeak'] = Decimal(0.0) reporting[energy_item_id]['onpeak'] = Decimal(0.0) reporting[energy_item_id]['midpeak'] = Decimal(0.0) reporting[energy_item_id]['offpeak'] = Decimal(0.0) cursor_energy.execute(" SELECT start_datetime_utc, actual_value " " FROM tbl_tenant_input_item_hourly " " WHERE tenant_id = %s " " AND energy_item_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s " " ORDER BY start_datetime_utc ", (tenant['id'], energy_item_id, reporting_start_datetime_utc, reporting_end_datetime_utc)) rows_tenant_hourly = cursor_energy.fetchall() rows_tenant_periodically = utilities.aggregate_hourly_data_by_period(rows_tenant_hourly, reporting_start_datetime_utc, reporting_end_datetime_utc, period_type) for row_tenant_periodically in rows_tenant_periodically: current_datetime_local = row_tenant_periodically[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) if period_type == 'hourly': current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') elif period_type == 'daily': current_datetime = current_datetime_local.strftime('%Y-%m-%d') elif period_type == 'monthly': current_datetime = current_datetime_local.strftime('%Y-%m') elif period_type == 'yearly': current_datetime = current_datetime_local.strftime('%Y') actual_value = Decimal(0.0) if row_tenant_periodically[1] is None else row_tenant_periodically[1] reporting[energy_item_id]['timestamps'].append(current_datetime) reporting[energy_item_id]['values'].append(actual_value) reporting[energy_item_id]['subtotal'] += actual_value energy_category_tariff_dict = \ utilities.get_energy_category_peak_types(tenant['cost_center_id'], energy_item_dict[energy_item_id]['energy_category_id'], reporting_start_datetime_utc, reporting_end_datetime_utc) for row in rows_tenant_hourly: peak_type = energy_category_tariff_dict.get(row[0], None) if peak_type == 'toppeak': reporting[energy_item_id]['toppeak'] += row[1] elif peak_type == 'onpeak': reporting[energy_item_id]['onpeak'] += row[1] elif peak_type == 'midpeak': reporting[energy_item_id]['midpeak'] += row[1] elif peak_type == 'offpeak': reporting[energy_item_id]['offpeak'] += row[1] ################################################################################################################ # Step 8: query tariff data ################################################################################################################ parameters_data = dict() parameters_data['names'] = list() parameters_data['timestamps'] = list() parameters_data['values'] = list() if energy_item_set is not None and len(energy_item_set) > 0: for energy_item_id in energy_item_set: energy_category_tariff_dict = \ utilities.get_energy_category_tariffs(tenant['cost_center_id'], energy_item_dict[energy_item_id]['energy_category_id'], reporting_start_datetime_utc, reporting_end_datetime_utc) tariff_timestamp_list = list() tariff_value_list = list() for k, v in energy_category_tariff_dict.items(): # convert k from utc to local k = k + timedelta(minutes=timezone_offset) tariff_timestamp_list.append(k.isoformat()[0:19][0:19]) tariff_value_list.append(v) parameters_data['names'].append('TARIFF-' + energy_item_dict[energy_item_id]['name']) parameters_data['timestamps'].append(tariff_timestamp_list) parameters_data['values'].append(tariff_value_list) ################################################################################################################ # Step 9: query associated sensors and points data ################################################################################################################ for point in point_list: point_values = [] point_timestamps = [] if point['object_type'] == 'ANALOG_VALUE': query = (" SELECT utc_date_time, actual_value " " FROM tbl_analog_value " " WHERE point_id = %s " " AND utc_date_time BETWEEN %s AND %s " " ORDER BY utc_date_time ") cursor_historical.execute(query, (point['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) rows = cursor_historical.fetchall() if rows is not None and len(rows) > 0: for row in rows: current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') point_timestamps.append(current_datetime) point_values.append(row[1]) elif point['object_type'] == 'ENERGY_VALUE': query = (" SELECT utc_date_time, actual_value " " FROM tbl_energy_value " " WHERE point_id = %s " " AND utc_date_time BETWEEN %s AND %s " " ORDER BY utc_date_time ") cursor_historical.execute(query, (point['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) rows = cursor_historical.fetchall() if rows is not None and len(rows) > 0: for row in rows: current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') point_timestamps.append(current_datetime) point_values.append(row[1]) elif point['object_type'] == 'DIGITAL_VALUE': query = (" SELECT utc_date_time, actual_value " " FROM tbl_digital_value " " WHERE point_id = %s " " AND utc_date_time BETWEEN %s AND %s ") cursor_historical.execute(query, (point['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) rows = cursor_historical.fetchall() if rows is not None and len(rows) > 0: for row in rows: current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') point_timestamps.append(current_datetime) point_values.append(row[1]) parameters_data['names'].append(point['name'] + ' (' + point['units'] + ')') parameters_data['timestamps'].append(point_timestamps) parameters_data['values'].append(point_values) ################################################################################################################ # Step 10: construct the report ################################################################################################################ if cursor_system: cursor_system.close() if cnx_system: cnx_system.disconnect() if cursor_energy: cursor_energy.close() if cnx_energy: cnx_energy.disconnect() result = dict() result['tenant'] = dict() result['tenant']['name'] = tenant['name'] result['tenant']['area'] = tenant['area'] result['base_period'] = dict() result['base_period']['names'] = list() result['base_period']['units'] = list() result['base_period']['timestamps'] = list() result['base_period']['values'] = list() result['base_period']['subtotals'] = list() if energy_item_set is not None and len(energy_item_set) > 0: for energy_item_id in energy_item_set: result['base_period']['names'].append(energy_item_dict[energy_item_id]['name']) result['base_period']['units'].append(energy_item_dict[energy_item_id]['unit_of_measure']) result['base_period']['timestamps'].append(base[energy_item_id]['timestamps']) result['base_period']['values'].append(base[energy_item_id]['values']) result['base_period']['subtotals'].append(base[energy_item_id]['subtotal']) result['reporting_period'] = dict() result['reporting_period']['names'] = list() result['reporting_period']['energy_item_ids'] = list() result['reporting_period']['energy_category_names'] = list() result['reporting_period']['energy_category_ids'] = list() result['reporting_period']['units'] = list() result['reporting_period']['timestamps'] = list() result['reporting_period']['values'] = list() result['reporting_period']['subtotals'] = list() result['reporting_period']['subtotals_per_unit_area'] = list() result['reporting_period']['toppeaks'] = list() result['reporting_period']['onpeaks'] = list() result['reporting_period']['midpeaks'] = list() result['reporting_period']['offpeaks'] = list() result['reporting_period']['increment_rates'] = list() if energy_item_set is not None and len(energy_item_set) > 0: for energy_item_id in energy_item_set: result['reporting_period']['names'].append(energy_item_dict[energy_item_id]['name']) result['reporting_period']['energy_item_ids'].append(energy_item_id) result['reporting_period']['energy_category_names'].append( energy_item_dict[energy_item_id]['energy_category_name']) result['reporting_period']['energy_category_ids'].append( energy_item_dict[energy_item_id]['energy_category_id']) result['reporting_period']['units'].append(energy_item_dict[energy_item_id]['unit_of_measure']) result['reporting_period']['timestamps'].append(reporting[energy_item_id]['timestamps']) result['reporting_period']['values'].append(reporting[energy_item_id]['values']) result['reporting_period']['subtotals'].append(reporting[energy_item_id]['subtotal']) result['reporting_period']['subtotals_per_unit_area'].append( reporting[energy_item_id]['subtotal'] / tenant['area'] if tenant['area'] > 0.0 else None) result['reporting_period']['toppeaks'].append(reporting[energy_item_id]['toppeak']) result['reporting_period']['onpeaks'].append(reporting[energy_item_id]['onpeak']) result['reporting_period']['midpeaks'].append(reporting[energy_item_id]['midpeak']) result['reporting_period']['offpeaks'].append(reporting[energy_item_id]['offpeak']) result['reporting_period']['increment_rates'].append( (reporting[energy_item_id]['subtotal'] - base[energy_item_id]['subtotal']) / base[energy_item_id]['subtotal'] if base[energy_item_id]['subtotal'] > 0.0 else None) result['parameters'] = { "names": parameters_data['names'], "timestamps": parameters_data['timestamps'], "values": parameters_data['values'] } resp.body = json.dumps(result)
def on_get(req, resp): print(req.params) meter_id = req.params.get('meterid') reporting_period_start_datetime_local = req.params.get( 'reportingperiodstartdatetime') reporting_period_end_datetime_local = req.params.get( 'reportingperiodenddatetime') ################################################################################################################ # Step 1: valid parameters ################################################################################################################ if meter_id is None: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_METER_ID') else: meter_id = str.strip(meter_id) if not meter_id.isdigit() or int(meter_id) <= 0: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_METER_ID') timezone_offset = int(config.utc_offset[1:3]) * 60 + int( config.utc_offset[4:6]) if config.utc_offset[0] == '-': timezone_offset = -timezone_offset if reporting_period_start_datetime_local is None: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_REPORTING_PERIOD_BEGINS_DATETIME") else: reporting_period_start_datetime_local = str.strip( reporting_period_start_datetime_local) try: reporting_start_datetime_utc = datetime.strptime( reporting_period_start_datetime_local, '%Y-%m-%dT%H:%M:%S') except ValueError: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_REPORTING_PERIOD_BEGINS_DATETIME") reporting_start_datetime_utc = reporting_start_datetime_utc.replace(tzinfo=timezone.utc) - \ timedelta(minutes=timezone_offset) if reporting_period_end_datetime_local is None: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_REPORTING_PERIOD_ENDS_DATETIME") else: reporting_period_end_datetime_local = str.strip( reporting_period_end_datetime_local) try: reporting_end_datetime_utc = datetime.strptime( reporting_period_end_datetime_local, '%Y-%m-%dT%H:%M:%S') except ValueError: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_REPORTING_PERIOD_ENDS_DATETIME") reporting_end_datetime_utc = reporting_end_datetime_utc.replace(tzinfo=timezone.utc) - \ timedelta(minutes=timezone_offset) if reporting_start_datetime_utc >= reporting_end_datetime_utc: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_REPORTING_PERIOD_ENDS_DATETIME') ################################################################################################################ # Step 2: query the meter and energy category ################################################################################################################ cnx_system = mysql.connector.connect(**config.myems_system_db) cursor_system = cnx_system.cursor() cnx_historical = mysql.connector.connect(**config.myems_historical_db) cursor_historical = cnx_historical.cursor() cursor_system.execute( " SELECT m.id, m.name, m.cost_center_id, m.energy_category_id, " " ec.name, ec.unit_of_measure, ec.kgce, ec.kgco2e " " FROM tbl_meters m, tbl_energy_categories ec " " WHERE m.id = %s AND m.energy_category_id = ec.id ", (meter_id, )) row_meter = cursor_system.fetchone() if row_meter is None: if cursor_system: cursor_system.close() if cnx_system: cnx_system.disconnect() if cursor_historical: cursor_historical.close() if cnx_historical: cnx_historical.disconnect() raise falcon.HTTPError(falcon.HTTP_404, title='API.NOT_FOUND', description='API.METER_NOT_FOUND') meter = dict() meter['id'] = row_meter[0] meter['name'] = row_meter[1] meter['cost_center_id'] = row_meter[2] meter['energy_category_id'] = row_meter[3] meter['energy_category_name'] = row_meter[4] meter['unit_of_measure'] = row_meter[5] meter['kgce'] = row_meter[6] meter['kgco2e'] = row_meter[7] ################################################################################################################ # Step 3: query associated points ################################################################################################################ point_list = list() cursor_system.execute( " SELECT p.id, p.name, p.units, p.object_type " " FROM tbl_meters m, tbl_meters_points mp, tbl_points p " " WHERE m.id = %s AND m.id = mp.meter_id AND mp.point_id = p.id " " ORDER BY p.id ", (meter['id'], )) rows_points = cursor_system.fetchall() if rows_points is not None and len(rows_points) > 0: for row in rows_points: point_list.append({ "id": row[0], "name": row[1], "units": row[2], "object_type": row[3] }) ################################################################################################################ # Step 4: query reporting period points trends ################################################################################################################ reporting = dict() reporting['names'] = list() reporting['timestamps'] = list() reporting['values'] = list() for point in point_list: point_values = [] point_timestamps = [] if point['object_type'] == 'ANALOG_VALUE': query = (" SELECT utc_date_time, actual_value " " FROM tbl_analog_value " " WHERE point_id = %s " " AND utc_date_time BETWEEN %s AND %s " " ORDER BY utc_date_time ") cursor_historical.execute( query, (point['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) rows = cursor_historical.fetchall() if rows is not None and len(rows) > 0: for row in rows: current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) current_datetime = current_datetime_local.strftime( '%Y-%m-%dT%H:%M:%S') point_timestamps.append(current_datetime) point_values.append(row[1]) elif point['object_type'] == 'ENERGY_VALUE': query = (" SELECT utc_date_time, actual_value " " FROM tbl_energy_value " " WHERE point_id = %s " " AND utc_date_time BETWEEN %s AND %s " " ORDER BY utc_date_time ") cursor_historical.execute( query, (point['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) rows = cursor_historical.fetchall() if rows is not None and len(rows) > 0: for row in rows: current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) current_datetime = current_datetime_local.strftime( '%Y-%m-%dT%H:%M:%S') point_timestamps.append(current_datetime) point_values.append(row[1]) elif point['object_type'] == 'DIGITAL_VALUE': query = (" SELECT utc_date_time, actual_value " " FROM tbl_digital_value " " WHERE point_id = %s " " AND utc_date_time BETWEEN %s AND %s ") cursor_historical.execute( query, (point['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) rows = cursor_historical.fetchall() if rows is not None and len(rows) > 0: for row in rows: current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) current_datetime = current_datetime_local.strftime( '%Y-%m-%dT%H:%M:%S') point_timestamps.append(current_datetime) point_values.append(row[1]) reporting['names'].append(point['name'] + ' (' + point['units'] + ')') reporting['timestamps'].append(point_timestamps) reporting['values'].append(point_values) ################################################################################################################ # Step 5: query tariff data ################################################################################################################ parameters_data = dict() parameters_data['names'] = list() parameters_data['timestamps'] = list() parameters_data['values'] = list() tariff_dict = utilities.get_energy_category_tariffs( meter['cost_center_id'], meter['energy_category_id'], reporting_start_datetime_utc, reporting_end_datetime_utc) print(tariff_dict) tariff_timestamp_list = list() tariff_value_list = list() for k, v in tariff_dict.items(): # convert k from utc to local k = k + timedelta(minutes=timezone_offset) tariff_timestamp_list.append(k.isoformat()[0:19]) tariff_value_list.append(v) parameters_data['names'].append('TARIFF-' + meter['energy_category_name']) parameters_data['timestamps'].append(tariff_timestamp_list) parameters_data['values'].append(tariff_value_list) ################################################################################################################ # Step 6: construct the report ################################################################################################################ if cursor_system: cursor_system.close() if cnx_system: cnx_system.disconnect() if cursor_historical: cursor_historical.close() if cnx_historical: cnx_historical.disconnect() result = { "meter": { "cost_center_id": meter['cost_center_id'], "energy_category_id": meter['energy_category_id'], "energy_category_name": meter['energy_category_name'], "unit_of_measure": meter['unit_of_measure'], "kgce": meter['kgce'], "kgco2e": meter['kgco2e'], }, "reporting_period": { "names": reporting['names'], "timestamps": reporting['timestamps'], "values": reporting['values'], }, "parameters": { "names": parameters_data['names'], "timestamps": parameters_data['timestamps'], "values": parameters_data['values'] }, } # export result to Excel file and then encode the file to base64 string result['excel_bytes_base64'] = excelexporters.metertrend.export( result, meter['name'], reporting_period_start_datetime_local, reporting_period_end_datetime_local, None) resp.body = json.dumps(result)
def on_get(req, resp): print(req.params) offline_meter_id = req.params.get('offlinemeterid') period_type = req.params.get('periodtype') base_period_start_datetime = req.params.get('baseperiodstartdatetime') base_period_end_datetime = req.params.get('baseperiodenddatetime') reporting_period_start_datetime = req.params.get( 'reportingperiodstartdatetime') reporting_period_end_datetime = req.params.get( 'reportingperiodenddatetime') ################################################################################################################ # Step 1: valid parameters ################################################################################################################ if offline_meter_id is None: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_OFFLINE_METER_ID') else: offline_meter_id = str.strip(offline_meter_id) if not offline_meter_id.isdigit() or int(offline_meter_id) <= 0: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_OFFLINE_METER_ID') if period_type is None: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_PERIOD_TYPE') else: period_type = str.strip(period_type) if period_type not in ['hourly', 'daily', 'monthly', 'yearly']: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_PERIOD_TYPE') timezone_offset = int(config.utc_offset[1:3]) * 60 + int( config.utc_offset[4:6]) if config.utc_offset[0] == '-': timezone_offset = -timezone_offset base_start_datetime_utc = None if base_period_start_datetime is not None and len( str.strip(base_period_start_datetime)) > 0: base_period_start_datetime = str.strip(base_period_start_datetime) try: base_start_datetime_utc = datetime.strptime( base_period_start_datetime, '%Y-%m-%dT%H:%M:%S') except ValueError: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_BASE_PERIOD_START_DATETIME") base_start_datetime_utc = base_start_datetime_utc.replace(tzinfo=timezone.utc) - \ timedelta(minutes=timezone_offset) base_end_datetime_utc = None if base_period_end_datetime is not None and len( str.strip(base_period_end_datetime)) > 0: base_period_end_datetime = str.strip(base_period_end_datetime) try: base_end_datetime_utc = datetime.strptime( base_period_end_datetime, '%Y-%m-%dT%H:%M:%S') except ValueError: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_BASE_PERIOD_END_DATETIME") base_end_datetime_utc = base_end_datetime_utc.replace(tzinfo=timezone.utc) - \ timedelta(minutes=timezone_offset) if base_start_datetime_utc is not None and base_end_datetime_utc is not None and \ base_start_datetime_utc >= base_end_datetime_utc: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_BASE_PERIOD_END_DATETIME') if reporting_period_start_datetime is None: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_REPORTING_PERIOD_START_DATETIME") else: reporting_period_start_datetime = str.strip( reporting_period_start_datetime) try: reporting_start_datetime_utc = datetime.strptime( reporting_period_start_datetime, '%Y-%m-%dT%H:%M:%S') except ValueError: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_REPORTING_PERIOD_START_DATETIME") reporting_start_datetime_utc = reporting_start_datetime_utc.replace(tzinfo=timezone.utc) - \ timedelta(minutes=timezone_offset) if reporting_period_end_datetime is None: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_REPORTING_PERIOD_END_DATETIME") else: reporting_period_end_datetime = str.strip( reporting_period_end_datetime) try: reporting_end_datetime_utc = datetime.strptime( reporting_period_end_datetime, '%Y-%m-%dT%H:%M:%S') except ValueError: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_REPORTING_PERIOD_END_DATETIME") reporting_end_datetime_utc = reporting_end_datetime_utc.replace(tzinfo=timezone.utc) - \ timedelta(minutes=timezone_offset) if reporting_start_datetime_utc >= reporting_end_datetime_utc: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_REPORTING_PERIOD_END_DATETIME') ################################################################################################################ # Step 2: query the offline meter and energy category ################################################################################################################ cnx_system = mysql.connector.connect(**config.myems_system_db) cursor_system = cnx_system.cursor() cnx_energy = mysql.connector.connect(**config.myems_energy_db) cursor_energy = cnx_energy.cursor() cursor_system.execute( " SELECT m.id, m.name, m.cost_center_id, m.energy_category_id, " " ec.name, ec.unit_of_measure, ec.kgce, ec.kgco2e " " FROM tbl_offline_meters m, tbl_energy_categories ec " " WHERE m.id = %s AND m.energy_category_id = ec.id ", (offline_meter_id, )) row_offline_meter = cursor_system.fetchone() if row_offline_meter is None: if cursor_system: cursor_system.close() if cnx_system: cnx_system.disconnect() if cursor_energy: cursor_energy.close() if cnx_energy: cnx_energy.disconnect() raise falcon.HTTPError(falcon.HTTP_404, title='API.NOT_FOUND', description='API.OFFLINE_METER_NOT_FOUND') offline_meter = dict() offline_meter['id'] = row_offline_meter[0] offline_meter['name'] = row_offline_meter[1] offline_meter['cost_center_id'] = row_offline_meter[2] offline_meter['energy_category_id'] = row_offline_meter[3] offline_meter['energy_category_name'] = row_offline_meter[4] offline_meter['unit_of_measure'] = row_offline_meter[5] offline_meter['kgce'] = row_offline_meter[6] offline_meter['kgco2e'] = row_offline_meter[7] ################################################################################################################ # Step 3: query base period energy consumption ################################################################################################################ query = (" SELECT start_datetime_utc, actual_value " " FROM tbl_offline_meter_hourly " " WHERE offline_meter_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s " " ORDER BY start_datetime_utc ") cursor_energy.execute(query, (offline_meter['id'], base_start_datetime_utc, base_end_datetime_utc)) rows_offline_meter_hourly = cursor_energy.fetchall() rows_offline_meter_periodically = utilities.aggregate_hourly_data_by_period( rows_offline_meter_hourly, base_start_datetime_utc, base_end_datetime_utc, period_type) base = dict() base['timestamps'] = list() base['values'] = list() base['total_in_category'] = Decimal(0.0) base['total_in_kgce'] = Decimal(0.0) base['total_in_kgco2e'] = Decimal(0.0) for row_offline_meter_periodically in rows_offline_meter_periodically: current_datetime_local = row_offline_meter_periodically[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) if period_type == 'hourly': current_datetime = current_datetime_local.strftime( '%Y-%m-%dT%H:%M:%S') elif period_type == 'daily': current_datetime = current_datetime_local.strftime('%Y-%m-%d') elif period_type == 'monthly': current_datetime = current_datetime_local.strftime('%Y-%m') elif period_type == 'yearly': current_datetime = current_datetime_local.strftime('%Y') actual_value = Decimal(0.0) if row_offline_meter_periodically[1] is None \ else row_offline_meter_periodically[1] base['timestamps'].append(current_datetime) base['values'].append(actual_value) base['total_in_category'] += actual_value base['total_in_kgce'] += actual_value * offline_meter['kgce'] base['total_in_kgco2e'] += actual_value * offline_meter['kgco2e'] ################################################################################################################ # Step 4: query reporting period energy consumption ################################################################################################################ query = (" SELECT start_datetime_utc, actual_value " " FROM tbl_offline_meter_hourly " " WHERE offline_meter_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s " " ORDER BY start_datetime_utc ") cursor_energy.execute( query, (offline_meter['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) rows_offline_meter_hourly = cursor_energy.fetchall() rows_offline_meter_periodically = utilities.aggregate_hourly_data_by_period( rows_offline_meter_hourly, reporting_start_datetime_utc, reporting_end_datetime_utc, period_type) reporting = dict() reporting['timestamps'] = list() reporting['values'] = list() reporting['total_in_category'] = Decimal(0.0) reporting['total_in_kgce'] = Decimal(0.0) reporting['total_in_kgco2e'] = Decimal(0.0) for row_offline_meter_periodically in rows_offline_meter_periodically: current_datetime_local = row_offline_meter_periodically[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) if period_type == 'hourly': current_datetime = current_datetime_local.strftime( '%Y-%m-%dT%H:%M:%S') elif period_type == 'daily': current_datetime = current_datetime_local.strftime('%Y-%m-%d') elif period_type == 'monthly': current_datetime = current_datetime_local.strftime('%Y-%m') elif period_type == 'yearly': current_datetime = current_datetime_local.strftime('%Y') actual_value = Decimal(0.0) if row_offline_meter_periodically[1] is None \ else row_offline_meter_periodically[1] reporting['timestamps'].append(current_datetime) reporting['values'].append(actual_value) reporting['total_in_category'] += actual_value reporting['total_in_kgce'] += actual_value * offline_meter['kgce'] reporting[ 'total_in_kgco2e'] += actual_value * offline_meter['kgco2e'] ################################################################################################################ # Step 5: query tariff data ################################################################################################################ parameters_data = dict() parameters_data['names'] = list() parameters_data['timestamps'] = list() parameters_data['values'] = list() tariff_dict = utilities.get_energy_category_tariffs( offline_meter['cost_center_id'], offline_meter['energy_category_id'], reporting_start_datetime_utc, reporting_end_datetime_utc) tariff_timestamp_list = list() tariff_value_list = list() for k, v in tariff_dict.items(): # convert k from utc to local k = k + timedelta(minutes=timezone_offset) tariff_timestamp_list.append(k.isoformat()[0:19]) tariff_value_list.append(v) parameters_data['names'].append('TARIFF-' + offline_meter['energy_category_name']) parameters_data['timestamps'].append(tariff_timestamp_list) parameters_data['values'].append(tariff_value_list) ################################################################################################################ # Step 6: construct the report ################################################################################################################ if cursor_system: cursor_system.close() if cnx_system: cnx_system.disconnect() if cursor_energy: cursor_energy.close() if cnx_energy: cnx_energy.disconnect() result = { "offline_meter": { "cost_center_id": offline_meter['cost_center_id'], "energy_category_id": offline_meter['energy_category_id'], "energy_category_name": offline_meter['energy_category_name'], "unit_of_measure": offline_meter['unit_of_measure'], "kgce": offline_meter['kgce'], "kgco2e": offline_meter['kgco2e'], }, "base_period": { "total_in_category": base['total_in_category'], "total_in_kgce": base['total_in_kgce'], "total_in_kgco2e": base['total_in_kgco2e'], "timestamps": base['timestamps'], "values": base['values'], }, "reporting_period": { "increment_rate": (reporting['total_in_category'] - base['total_in_category']) / base['total_in_category'] if base['total_in_category'] > 0 else None, "total_in_category": reporting['total_in_category'], "total_in_kgce": reporting['total_in_kgce'], "total_in_kgco2e": reporting['total_in_kgco2e'], "timestamps": reporting['timestamps'], "values": reporting['values'], }, "parameters": { "names": parameters_data['names'], "timestamps": parameters_data['timestamps'], "values": parameters_data['values'] }, } # export result to Excel file and then encode the file to base64 string result['excel_bytes_base64'] = \ excelexporters.offlinemeterenergy.export(result, offline_meter['name'], reporting_period_start_datetime, reporting_period_end_datetime, period_type) resp.body = json.dumps(result)
def on_get(req, resp): print(req.params) equipment_id = req.params.get('equipmentid') period_type = req.params.get('periodtype') base_start_datetime_local = req.params.get('baseperiodstartdatetime') base_end_datetime_local = req.params.get('baseperiodenddatetime') reporting_start_datetime_local = req.params.get( 'reportingperiodstartdatetime') reporting_end_datetime_local = req.params.get( 'reportingperiodenddatetime') ################################################################################################################ # Step 1: valid parameters ################################################################################################################ if equipment_id is None: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_EQUIPMENT_ID') else: equipment_id = str.strip(equipment_id) if not equipment_id.isdigit() or int(equipment_id) <= 0: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_EQUIPMENT_ID') if period_type is None: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_PERIOD_TYPE') else: period_type = str.strip(period_type) if period_type not in ['hourly', 'daily', 'monthly', 'yearly']: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_PERIOD_TYPE') timezone_offset = int(config.utc_offset[1:3]) * 60 + int( config.utc_offset[4:6]) if config.utc_offset[0] == '-': timezone_offset = -timezone_offset base_start_datetime_utc = None if base_start_datetime_local is not None and len( str.strip(base_start_datetime_local)) > 0: base_start_datetime_local = str.strip(base_start_datetime_local) try: base_start_datetime_utc = datetime.strptime(base_start_datetime_local, '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ timedelta(minutes=timezone_offset) except ValueError: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_BASE_PERIOD_START_DATETIME") base_end_datetime_utc = None if base_end_datetime_local is not None and len( str.strip(base_end_datetime_local)) > 0: base_end_datetime_local = str.strip(base_end_datetime_local) try: base_end_datetime_utc = datetime.strptime(base_end_datetime_local, '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ timedelta(minutes=timezone_offset) except ValueError: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_BASE_PERIOD_END_DATETIME") if base_start_datetime_utc is not None and base_end_datetime_utc is not None and \ base_start_datetime_utc >= base_end_datetime_utc: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_BASE_PERIOD_END_DATETIME') if reporting_start_datetime_local is None: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_REPORTING_PERIOD_START_DATETIME") else: reporting_start_datetime_local = str.strip( reporting_start_datetime_local) try: reporting_start_datetime_utc = datetime.strptime(reporting_start_datetime_local, '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ timedelta(minutes=timezone_offset) except ValueError: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_REPORTING_PERIOD_START_DATETIME") if reporting_end_datetime_local is None: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_REPORTING_PERIOD_END_DATETIME") else: reporting_end_datetime_local = str.strip( reporting_end_datetime_local) try: reporting_end_datetime_utc = datetime.strptime(reporting_end_datetime_local, '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ timedelta(minutes=timezone_offset) except ValueError: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_REPORTING_PERIOD_END_DATETIME") if reporting_start_datetime_utc >= reporting_end_datetime_utc: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_REPORTING_PERIOD_END_DATETIME') ################################################################################################################ # Step 2: query the equipment ################################################################################################################ cnx_system = mysql.connector.connect(**config.myems_system_db) cursor_system = cnx_system.cursor() cnx_energy = mysql.connector.connect(**config.myems_energy_db) cursor_energy = cnx_energy.cursor() cnx_historical = mysql.connector.connect(**config.myems_historical_db) cursor_historical = cnx_historical.cursor() cursor_system.execute( " SELECT id, name, cost_center_id " " FROM tbl_equipments " " WHERE id = %s ", (equipment_id, )) row_equipment = cursor_system.fetchone() if row_equipment is None: if cursor_system: cursor_system.close() if cnx_system: cnx_system.disconnect() if cursor_energy: cursor_energy.close() if cnx_energy: cnx_energy.disconnect() if cnx_historical: cnx_historical.close() if cursor_historical: cursor_historical.disconnect() raise falcon.HTTPError(falcon.HTTP_404, title='API.NOT_FOUND', description='API.EQUIPMENT_NOT_FOUND') equipment = dict() equipment['id'] = row_equipment[0] equipment['name'] = row_equipment[1] equipment['cost_center_id'] = row_equipment[2] ################################################################################################################ # Step 3: query input energy categories and output energy categories ################################################################################################################ energy_category_set_input = set() energy_category_set_output = set() # query input energy categories in base period cursor_energy.execute( " SELECT DISTINCT(energy_category_id) " " FROM tbl_equipment_input_category_hourly " " WHERE equipment_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s ", (equipment['id'], base_start_datetime_utc, base_end_datetime_utc)) rows_energy_categories = cursor_energy.fetchall() if rows_energy_categories is not None or len( rows_energy_categories) > 0: for row_energy_category in rows_energy_categories: energy_category_set_input.add(row_energy_category[0]) # query input energy categories in reporting period cursor_energy.execute( " SELECT DISTINCT(energy_category_id) " " FROM tbl_equipment_input_category_hourly " " WHERE equipment_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s ", (equipment['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) rows_energy_categories = cursor_energy.fetchall() if rows_energy_categories is not None or len( rows_energy_categories) > 0: for row_energy_category in rows_energy_categories: energy_category_set_input.add(row_energy_category[0]) # query output energy categories in base period cursor_energy.execute( " SELECT DISTINCT(energy_category_id) " " FROM tbl_equipment_output_category_hourly " " WHERE equipment_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s ", (equipment['id'], base_start_datetime_utc, base_end_datetime_utc)) rows_energy_categories = cursor_energy.fetchall() if rows_energy_categories is not None or len( rows_energy_categories) > 0: for row_energy_category in rows_energy_categories: energy_category_set_output.add(row_energy_category[0]) # query output energy categories in reporting period cursor_energy.execute( " SELECT DISTINCT(energy_category_id) " " FROM tbl_equipment_output_category_hourly " " WHERE equipment_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s ", (equipment['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) rows_energy_categories = cursor_energy.fetchall() if rows_energy_categories is not None or len( rows_energy_categories) > 0: for row_energy_category in rows_energy_categories: energy_category_set_output.add(row_energy_category[0]) # query properties of all energy categories above cursor_system.execute( " SELECT id, name, unit_of_measure, kgce, kgco2e " " FROM tbl_energy_categories " " ORDER BY id ", ) rows_energy_categories = cursor_system.fetchall() if rows_energy_categories is None or len(rows_energy_categories) == 0: if cursor_system: cursor_system.close() if cnx_system: cnx_system.disconnect() if cursor_energy: cursor_energy.close() if cnx_energy: cnx_energy.disconnect() if cnx_historical: cnx_historical.close() if cursor_historical: cursor_historical.disconnect() raise falcon.HTTPError(falcon.HTTP_404, title='API.NOT_FOUND', description='API.ENERGY_CATEGORY_NOT_FOUND') energy_category_dict = dict() for row_energy_category in rows_energy_categories: if row_energy_category[0] in energy_category_set_input or \ row_energy_category[0] in energy_category_set_output: energy_category_dict[row_energy_category[0]] = { "name": row_energy_category[1], "unit_of_measure": row_energy_category[2], "kgce": row_energy_category[3], "kgco2e": row_energy_category[4] } ################################################################################################################ # Step 4: query associated points ################################################################################################################ point_list = list() cursor_system.execute( " SELECT p.id, p.name, p.units, p.object_type " " FROM tbl_equipments e, tbl_equipments_parameters ep, tbl_points p " " WHERE e.id = %s AND e.id = ep.equipment_id AND ep.parameter_type = 'point' " " AND ep.point_id = p.id " " ORDER BY p.id ", (equipment['id'], )) rows_points = cursor_system.fetchall() if rows_points is not None and len(rows_points) > 0: for row in rows_points: point_list.append({ "id": row[0], "name": row[1], "units": row[2], "object_type": row[3] }) ################################################################################################################ # Step 5: query base period energy input ################################################################################################################ base_input = dict() if energy_category_set_input is not None and len( energy_category_set_input) > 0: for energy_category_id in energy_category_set_input: base_input[energy_category_id] = dict() base_input[energy_category_id]['timestamps'] = list() base_input[energy_category_id]['values'] = list() base_input[energy_category_id]['subtotal'] = Decimal(0.0) cursor_energy.execute( " SELECT start_datetime_utc, actual_value " " FROM tbl_equipment_input_category_hourly " " WHERE equipment_id = %s " " AND energy_category_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s " " ORDER BY start_datetime_utc ", (equipment['id'], energy_category_id, base_start_datetime_utc, base_end_datetime_utc)) rows_equipment_hourly = cursor_energy.fetchall() rows_equipment_periodically = utilities.aggregate_hourly_data_by_period( rows_equipment_hourly, base_start_datetime_utc, base_end_datetime_utc, period_type) for row_equipment_periodically in rows_equipment_periodically: current_datetime_local = row_equipment_periodically[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) if period_type == 'hourly': current_datetime = current_datetime_local.strftime( '%Y-%m-%dT%H:%M:%S') elif period_type == 'daily': current_datetime = current_datetime_local.strftime( '%Y-%m-%d') elif period_type == 'monthly': current_datetime = current_datetime_local.strftime( '%Y-%m') elif period_type == 'yearly': current_datetime = current_datetime_local.strftime( '%Y') actual_value = Decimal(0.0) if row_equipment_periodically[1] is None \ else row_equipment_periodically[1] base_input[energy_category_id]['timestamps'].append( current_datetime) base_input[energy_category_id]['values'].append( actual_value) base_input[energy_category_id]['subtotal'] += actual_value ################################################################################################################ # Step 6: query base period energy output ################################################################################################################ base_output = dict() if energy_category_set_output is not None and len( energy_category_set_output) > 0: for energy_category_id in energy_category_set_output: base_output[energy_category_id] = dict() base_output[energy_category_id]['timestamps'] = list() base_output[energy_category_id]['values'] = list() base_output[energy_category_id]['subtotal'] = Decimal(0.0) cursor_energy.execute( " SELECT start_datetime_utc, actual_value " " FROM tbl_equipment_output_category_hourly " " WHERE equipment_id = %s " " AND energy_category_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s " " ORDER BY start_datetime_utc ", (equipment['id'], energy_category_id, base_start_datetime_utc, base_end_datetime_utc)) rows_equipment_hourly = cursor_energy.fetchall() rows_equipment_periodically = utilities.aggregate_hourly_data_by_period( rows_equipment_hourly, base_start_datetime_utc, base_end_datetime_utc, period_type) for row_equipment_periodically in rows_equipment_periodically: current_datetime_local = row_equipment_periodically[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) if period_type == 'hourly': current_datetime = current_datetime_local.strftime( '%Y-%m-%dT%H:%M:%S') elif period_type == 'daily': current_datetime = current_datetime_local.strftime( '%Y-%m-%d') elif period_type == 'monthly': current_datetime = current_datetime_local.strftime( '%Y-%m') elif period_type == 'yearly': current_datetime = current_datetime_local.strftime( '%Y') actual_value = Decimal(0.0) if row_equipment_periodically[1] is None \ else row_equipment_periodically[1] base_output[energy_category_id]['timestamps'].append( current_datetime) base_output[energy_category_id]['values'].append( actual_value) base_output[energy_category_id]['subtotal'] += actual_value ################################################################################################################ # Step 7: query reporting period energy input ################################################################################################################ reporting_input = dict() if energy_category_set_input is not None and len( energy_category_set_input) > 0: for energy_category_id in energy_category_set_input: reporting_input[energy_category_id] = dict() reporting_input[energy_category_id]['timestamps'] = list() reporting_input[energy_category_id]['values'] = list() reporting_input[energy_category_id]['subtotal'] = Decimal(0.0) cursor_energy.execute( " SELECT start_datetime_utc, actual_value " " FROM tbl_equipment_input_category_hourly " " WHERE equipment_id = %s " " AND energy_category_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s " " ORDER BY start_datetime_utc ", (equipment['id'], energy_category_id, reporting_start_datetime_utc, reporting_end_datetime_utc)) rows_equipment_hourly = cursor_energy.fetchall() rows_equipment_periodically = utilities.aggregate_hourly_data_by_period( rows_equipment_hourly, reporting_start_datetime_utc, reporting_end_datetime_utc, period_type) for row_equipment_periodically in rows_equipment_periodically: current_datetime_local = row_equipment_periodically[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) if period_type == 'hourly': current_datetime = current_datetime_local.strftime( '%Y-%m-%dT%H:%M:%S') elif period_type == 'daily': current_datetime = current_datetime_local.strftime( '%Y-%m-%d') elif period_type == 'monthly': current_datetime = current_datetime_local.strftime( '%Y-%m') elif period_type == 'yearly': current_datetime = current_datetime_local.strftime( '%Y') actual_value = Decimal(0.0) if row_equipment_periodically[1] is None \ else row_equipment_periodically[1] reporting_input[energy_category_id]['timestamps'].append( current_datetime) reporting_input[energy_category_id]['values'].append( actual_value) reporting_input[energy_category_id][ 'subtotal'] += actual_value ################################################################################################################ # Step 8: query reporting period energy output ################################################################################################################ reporting_output = dict() if energy_category_set_output is not None and len( energy_category_set_output) > 0: for energy_category_id in energy_category_set_output: reporting_output[energy_category_id] = dict() reporting_output[energy_category_id]['timestamps'] = list() reporting_output[energy_category_id]['values'] = list() reporting_output[energy_category_id]['subtotal'] = Decimal(0.0) cursor_energy.execute( " SELECT start_datetime_utc, actual_value " " FROM tbl_equipment_output_category_hourly " " WHERE equipment_id = %s " " AND energy_category_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s " " ORDER BY start_datetime_utc ", (equipment['id'], energy_category_id, reporting_start_datetime_utc, reporting_end_datetime_utc)) rows_equipment_hourly = cursor_energy.fetchall() rows_equipment_periodically = utilities.aggregate_hourly_data_by_period( rows_equipment_hourly, reporting_start_datetime_utc, reporting_end_datetime_utc, period_type) for row_equipment_periodically in rows_equipment_periodically: current_datetime_local = row_equipment_periodically[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) if period_type == 'hourly': current_datetime = current_datetime_local.strftime( '%Y-%m-%dT%H:%M:%S') elif period_type == 'daily': current_datetime = current_datetime_local.strftime( '%Y-%m-%d') elif period_type == 'monthly': current_datetime = current_datetime_local.strftime( '%Y-%m') elif period_type == 'yearly': current_datetime = current_datetime_local.strftime( '%Y') actual_value = Decimal(0.0) if row_equipment_periodically[1] is None \ else row_equipment_periodically[1] reporting_output[energy_category_id]['timestamps'].append( current_datetime) reporting_output[energy_category_id]['values'].append( actual_value) reporting_output[energy_category_id][ 'subtotal'] += actual_value ################################################################################################################ # Step 9: query tariff data ################################################################################################################ parameters_data = dict() parameters_data['names'] = list() parameters_data['timestamps'] = list() parameters_data['values'] = list() if energy_category_set_input is not None and len( energy_category_set_input) > 0: for energy_category_id in energy_category_set_input: energy_category_tariff_dict = utilities.get_energy_category_tariffs( equipment['cost_center_id'], energy_category_id, reporting_start_datetime_utc, reporting_end_datetime_utc) tariff_timestamp_list = list() tariff_value_list = list() for k, v in energy_category_tariff_dict.items(): # convert k from utc to local k = k + timedelta(minutes=timezone_offset) tariff_timestamp_list.append(k.isoformat()[0:19][0:19]) tariff_value_list.append(v) parameters_data['names'].append( 'TARIFF-' + energy_category_dict[energy_category_id]['name']) parameters_data['timestamps'].append(tariff_timestamp_list) parameters_data['values'].append(tariff_value_list) ################################################################################################################ # Step 10: query associated sensors and points data ################################################################################################################ for point in point_list: point_values = [] point_timestamps = [] if point['object_type'] == 'ANALOG_VALUE': query = (" SELECT utc_date_time, actual_value " " FROM tbl_analog_value " " WHERE point_id = %s " " AND utc_date_time BETWEEN %s AND %s " " ORDER BY utc_date_time ") cursor_historical.execute( query, (point['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) rows = cursor_historical.fetchall() if rows is not None and len(rows) > 0: for row in rows: current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) current_datetime = current_datetime_local.strftime( '%Y-%m-%dT%H:%M:%S') point_timestamps.append(current_datetime) point_values.append(row[1]) elif point['object_type'] == 'ENERGY_VALUE': query = (" SELECT utc_date_time, actual_value " " FROM tbl_energy_value " " WHERE point_id = %s " " AND utc_date_time BETWEEN %s AND %s " " ORDER BY utc_date_time ") cursor_historical.execute( query, (point['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) rows = cursor_historical.fetchall() if rows is not None and len(rows) > 0: for row in rows: current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) current_datetime = current_datetime_local.strftime( '%Y-%m-%dT%H:%M:%S') point_timestamps.append(current_datetime) point_values.append(row[1]) elif point['object_type'] == 'DIGITAL_VALUE': query = (" SELECT utc_date_time, actual_value " " FROM tbl_digital_value " " WHERE point_id = %s " " AND utc_date_time BETWEEN %s AND %s ") cursor_historical.execute( query, (point['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) rows = cursor_historical.fetchall() if rows is not None and len(rows) > 0: for row in rows: current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) current_datetime = current_datetime_local.strftime( '%Y-%m-%dT%H:%M:%S') point_timestamps.append(current_datetime) point_values.append(row[1]) parameters_data['names'].append(point['name'] + ' (' + point['units'] + ')') parameters_data['timestamps'].append(point_timestamps) parameters_data['values'].append(point_values) ################################################################################################################ # Step 11: construct the report ################################################################################################################ if cursor_system: cursor_system.close() if cnx_system: cnx_system.disconnect() if cursor_energy: cursor_energy.close() if cnx_energy: cnx_energy.disconnect() result = dict() result['equipment'] = dict() result['equipment']['name'] = equipment['name'] result['base_period_input'] = dict() result['base_period_input']['names'] = list() result['base_period_input']['units'] = list() result['base_period_input']['timestamps'] = list() result['base_period_input']['values'] = list() result['base_period_input']['subtotals'] = list() if energy_category_set_input is not None and len( energy_category_set_input) > 0: for energy_category_id in energy_category_set_input: result['base_period_input']['names'].append( energy_category_dict[energy_category_id]['name']) result['base_period_input']['units'].append( energy_category_dict[energy_category_id] ['unit_of_measure']) result['base_period_input']['timestamps'].append( base_input[energy_category_id]['timestamps']) result['base_period_input']['values'].append( base_input[energy_category_id]['values']) result['base_period_input']['subtotals'].append( base_input[energy_category_id]['subtotal']) result['base_period_output'] = dict() result['base_period_output']['names'] = list() result['base_period_output']['units'] = list() result['base_period_output']['timestamps'] = list() result['base_period_output']['values'] = list() result['base_period_output']['subtotals'] = list() if energy_category_set_output is not None and len( energy_category_set_output) > 0: for energy_category_id in energy_category_set_output: result['base_period_output']['names'].append( energy_category_dict[energy_category_id]['name']) result['base_period_output']['units'].append( energy_category_dict[energy_category_id] ['unit_of_measure']) result['base_period_output']['timestamps'].append( base_output[energy_category_id]['timestamps']) result['base_period_output']['values'].append( base_output[energy_category_id]['values']) result['base_period_output']['subtotals'].append( base_output[energy_category_id]['subtotal']) result['base_period_efficiency'] = dict() result['base_period_efficiency']['names'] = list() result['base_period_efficiency']['units'] = list() result['base_period_efficiency']['timestamps'] = list() result['base_period_efficiency']['values'] = list() result['base_period_efficiency']['cumulations'] = list() if energy_category_set_output is not None and len( energy_category_set_output) > 0: for energy_category_id_output in energy_category_set_output: for energy_category_id_input in energy_category_set_input: result['base_period_efficiency']['names'].append( energy_category_dict[energy_category_id_output]['name'] + '/' + energy_category_dict[energy_category_id_input]['name']) result['base_period_efficiency']['units'].append( energy_category_dict[energy_category_id_output] ['unit_of_measure'] + '/' + energy_category_dict[energy_category_id_input] ['unit_of_measure']) result['base_period_efficiency']['timestamps'].append( base_output[energy_category_id_output]['timestamps']) efficiency_values = list() for i in range( len(base_output[energy_category_id_output] ['timestamps'])): efficiency_values.append(( base_output[energy_category_id_output]['values'][i] / base_input[energy_category_id_input]['values'][i] ) if base_input[energy_category_id_input]['values'][i] > Decimal(0.0) else None) result['base_period_efficiency']['values'].append( efficiency_values) base_cumulation = (base_output[energy_category_id_output]['subtotal'] / base_input[energy_category_id_input]['subtotal']) if \ base_input[energy_category_id_input]['subtotal'] > Decimal(0.0) else None result['base_period_efficiency']['cumulations'].append( base_cumulation) result['reporting_period_input'] = dict() result['reporting_period_input']['names'] = list() result['reporting_period_input']['energy_category_ids'] = list() result['reporting_period_input']['units'] = list() result['reporting_period_input']['timestamps'] = list() result['reporting_period_input']['values'] = list() result['reporting_period_input']['subtotals'] = list() result['reporting_period_input']['increment_rates'] = list() if energy_category_set_input is not None and len( energy_category_set_input) > 0: for energy_category_id in energy_category_set_input: result['reporting_period_input']['names'].append( energy_category_dict[energy_category_id]['name']) result['reporting_period_input']['energy_category_ids'].append( energy_category_id) result['reporting_period_input']['units'].append( energy_category_dict[energy_category_id] ['unit_of_measure']) result['reporting_period_input']['timestamps'].append( reporting_input[energy_category_id]['timestamps']) result['reporting_period_input']['values'].append( reporting_input[energy_category_id]['values']) result['reporting_period_input']['subtotals'].append( reporting_input[energy_category_id]['subtotal']) result['reporting_period_input']['increment_rates'].append( (reporting_input[energy_category_id]['subtotal'] - base_input[energy_category_id]['subtotal']) / base_input[energy_category_id]['subtotal'] if base_input[energy_category_id]['subtotal'] > 0.0 else None) result['reporting_period_output'] = dict() result['reporting_period_output']['names'] = list() result['reporting_period_output']['energy_category_ids'] = list() result['reporting_period_output']['units'] = list() result['reporting_period_output']['timestamps'] = list() result['reporting_period_output']['values'] = list() result['reporting_period_output']['subtotals'] = list() result['reporting_period_output']['increment_rates'] = list() if energy_category_set_output is not None and len( energy_category_set_output) > 0: for energy_category_id in energy_category_set_output: result['reporting_period_output']['names'].append( energy_category_dict[energy_category_id]['name']) result['reporting_period_output'][ 'energy_category_ids'].append(energy_category_id) result['reporting_period_output']['units'].append( energy_category_dict[energy_category_id] ['unit_of_measure']) result['reporting_period_output']['timestamps'].append( reporting_output[energy_category_id]['timestamps']) result['reporting_period_output']['values'].append( reporting_output[energy_category_id]['values']) result['reporting_period_output']['subtotals'].append( reporting_output[energy_category_id]['subtotal']) result['reporting_period_output']['increment_rates'].append( (reporting_output[energy_category_id]['subtotal'] - base_output[energy_category_id]['subtotal']) / base_output[energy_category_id]['subtotal'] if base_output[energy_category_id]['subtotal'] > 0.0 else None ) result['reporting_period_efficiency'] = dict() result['reporting_period_efficiency']['names'] = list() result['reporting_period_efficiency']['units'] = list() result['reporting_period_efficiency']['timestamps'] = list() result['reporting_period_efficiency']['values'] = list() result['reporting_period_efficiency']['cumulations'] = list() result['reporting_period_efficiency']['increment_rates'] = list() if energy_category_set_output is not None and len( energy_category_set_output) > 0: for energy_category_id_output in energy_category_set_output: for energy_category_id_input in energy_category_set_input: result['reporting_period_efficiency']['names'].append( energy_category_dict[energy_category_id_output]['name'] + '/' + energy_category_dict[energy_category_id_input]['name']) result['reporting_period_efficiency']['units'].append( energy_category_dict[energy_category_id_output] ['unit_of_measure'] + '/' + energy_category_dict[energy_category_id_input] ['unit_of_measure']) result['reporting_period_efficiency']['timestamps'].append( reporting_output[energy_category_id_output] ['timestamps']) efficiency_values = list() for i in range( len(reporting_output[energy_category_id_output] ['timestamps'])): efficiency_values.append( (reporting_output[energy_category_id_output] ['values'][i] / reporting_input[energy_category_id_input] ['values'][i] ) if reporting_input[energy_category_id_input] ['values'][i] > Decimal(0.0) else None) result['reporting_period_efficiency']['values'].append( efficiency_values) base_cumulation = (base_output[energy_category_id_output]['subtotal'] / base_input[energy_category_id_input]['subtotal']) if \ base_input[energy_category_id_input]['subtotal'] > Decimal(0.0) else None reporting_cumulation = (reporting_output[energy_category_id_output]['subtotal'] / reporting_input[energy_category_id_input]['subtotal']) if \ reporting_input[energy_category_id_input]['subtotal'] > Decimal(0.0) else None result['reporting_period_efficiency'][ 'cumulations'].append(reporting_cumulation) result['reporting_period_efficiency'][ 'increment_rates'].append( ((reporting_cumulation - base_cumulation) / base_cumulation if (base_cumulation is not None and base_cumulation > Decimal(0.0)) else None)) result['parameters'] = { "names": parameters_data['names'], "timestamps": parameters_data['timestamps'], "values": parameters_data['values'] } resp.body = json.dumps(result)
def on_get(req, resp): print(req.params) space_id = req.params.get('spaceid') period_type = req.params.get('periodtype') base_start_datetime_local = req.params.get('baseperiodstartdatetime') base_end_datetime_local = req.params.get('baseperiodenddatetime') reporting_start_datetime_local = req.params.get( 'reportingperiodstartdatetime') reporting_end_datetime_local = req.params.get( 'reportingperiodenddatetime') ################################################################################################################ # Step 1: valid parameters ################################################################################################################ if space_id is None: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_SPACE_ID') else: space_id = str.strip(space_id) if not space_id.isdigit() or int(space_id) <= 0: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_SPACE_ID') if period_type is None: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_PERIOD_TYPE') else: period_type = str.strip(period_type) if period_type not in ['hourly', 'daily', 'monthly', 'yearly']: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_PERIOD_TYPE') timezone_offset = int(config.utc_offset[1:3]) * 60 + int( config.utc_offset[4:6]) if config.utc_offset[0] == '-': timezone_offset = -timezone_offset base_start_datetime_utc = None if base_start_datetime_local is not None and len( str.strip(base_start_datetime_local)) > 0: base_start_datetime_local = str.strip(base_start_datetime_local) try: base_start_datetime_utc = datetime.strptime(base_start_datetime_local, '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ timedelta(minutes=timezone_offset) except ValueError: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_BASE_PERIOD_START_DATETIME") base_end_datetime_utc = None if base_end_datetime_local is not None and len( str.strip(base_end_datetime_local)) > 0: base_end_datetime_local = str.strip(base_end_datetime_local) try: base_end_datetime_utc = datetime.strptime(base_end_datetime_local, '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ timedelta(minutes=timezone_offset) except ValueError: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_BASE_PERIOD_END_DATETIME") if base_start_datetime_utc is not None and base_end_datetime_utc is not None and \ base_start_datetime_utc >= base_end_datetime_utc: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_BASE_PERIOD_END_DATETIME') if reporting_start_datetime_local is None: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_REPORTING_PERIOD_START_DATETIME") else: reporting_start_datetime_local = str.strip( reporting_start_datetime_local) try: reporting_start_datetime_utc = datetime.strptime(reporting_start_datetime_local, '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ timedelta(minutes=timezone_offset) except ValueError: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_REPORTING_PERIOD_START_DATETIME") if reporting_end_datetime_local is None: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_REPORTING_PERIOD_END_DATETIME") else: reporting_end_datetime_local = str.strip( reporting_end_datetime_local) try: reporting_end_datetime_utc = datetime.strptime(reporting_end_datetime_local, '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ timedelta(minutes=timezone_offset) except ValueError: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_REPORTING_PERIOD_END_DATETIME") if reporting_start_datetime_utc >= reporting_end_datetime_utc: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_REPORTING_PERIOD_END_DATETIME') ################################################################################################################ # Step 2: query the space ################################################################################################################ cnx_system = mysql.connector.connect(**config.myems_system_db) cursor_system = cnx_system.cursor() cnx_billing = mysql.connector.connect(**config.myems_billing_db) cursor_billing = cnx_billing.cursor() cnx_historical = mysql.connector.connect(**config.myems_historical_db) cursor_historical = cnx_historical.cursor() cursor_system.execute( " SELECT id, name, area, cost_center_id " " FROM tbl_spaces " " WHERE id = %s ", (space_id, )) row_space = cursor_system.fetchone() if row_space is None: if cursor_system: cursor_system.close() if cnx_system: cnx_system.disconnect() if cursor_billing: cursor_billing.close() if cnx_billing: cnx_billing.disconnect() if cnx_historical: cnx_historical.close() if cursor_historical: cursor_historical.disconnect() raise falcon.HTTPError(falcon.HTTP_404, title='API.NOT_FOUND', description='API.SPACE_NOT_FOUND') space = dict() space['id'] = row_space[0] space['name'] = row_space[1] space['area'] = row_space[2] space['cost_center_id'] = row_space[3] ################################################################################################################ # Step 3: query energy categories ################################################################################################################ energy_category_set = set() # query energy categories in base period cursor_billing.execute( " SELECT DISTINCT(energy_category_id) " " FROM tbl_space_input_category_hourly " " WHERE space_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s ", (space['id'], base_start_datetime_utc, base_end_datetime_utc)) rows_energy_categories = cursor_billing.fetchall() if rows_energy_categories is not None or len( rows_energy_categories) > 0: for row_energy_category in rows_energy_categories: energy_category_set.add(row_energy_category[0]) # query energy categories in reporting period cursor_billing.execute( " SELECT DISTINCT(energy_category_id) " " FROM tbl_space_input_category_hourly " " WHERE space_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s ", (space['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) rows_energy_categories = cursor_billing.fetchall() if rows_energy_categories is not None or len( rows_energy_categories) > 0: for row_energy_category in rows_energy_categories: energy_category_set.add(row_energy_category[0]) # query all energy categories in base period and reporting period cursor_system.execute( " SELECT id, name, unit_of_measure, kgce, kgco2e " " FROM tbl_energy_categories " " ORDER BY id ", ) rows_energy_categories = cursor_system.fetchall() if rows_energy_categories is None or len(rows_energy_categories) == 0: if cursor_system: cursor_system.close() if cnx_system: cnx_system.disconnect() if cursor_billing: cursor_billing.close() if cnx_billing: cnx_billing.disconnect() if cnx_historical: cnx_historical.close() if cursor_historical: cursor_historical.disconnect() raise falcon.HTTPError(falcon.HTTP_404, title='API.NOT_FOUND', description='API.ENERGY_CATEGORY_NOT_FOUND') energy_category_dict = dict() for row_energy_category in rows_energy_categories: if row_energy_category[0] in energy_category_set: energy_category_dict[row_energy_category[0]] = { "name": row_energy_category[1], "unit_of_measure": row_energy_category[2], "kgce": row_energy_category[3], "kgco2e": row_energy_category[4] } ################################################################################################################ # Step 4: query associated sensors ################################################################################################################ point_list = list() cursor_system.execute( " SELECT po.id, po.name, po.units, po.object_type " " FROM tbl_spaces sp, tbl_sensors se, tbl_spaces_sensors spse, " " tbl_points po, tbl_sensors_points sepo " " WHERE sp.id = %s AND sp.id = spse.space_id AND spse.sensor_id = se.id " " AND se.id = sepo.sensor_id AND sepo.point_id = po.id " " ORDER BY po.id ", (space['id'], )) rows_points = cursor_system.fetchall() if rows_points is not None and len(rows_points) > 0: for row in rows_points: point_list.append({ "id": row[0], "name": row[1], "units": row[2], "object_type": row[3] }) ################################################################################################################ # Step 5: query associated points ################################################################################################################ cursor_system.execute( " SELECT po.id, po.name, po.units, po.object_type " " FROM tbl_spaces sp, tbl_spaces_points sppo, tbl_points po " " WHERE sp.id = %s AND sp.id = sppo.space_id AND sppo.point_id = po.id " " ORDER BY po.id ", (space['id'], )) rows_points = cursor_system.fetchall() if rows_points is not None and len(rows_points) > 0: for row in rows_points: point_list.append({ "id": row[0], "name": row[1], "units": row[2], "object_type": row[3] }) ################################################################################################################ # Step 6: query child spaces ################################################################################################################ child_space_list = list() cursor_system.execute( " SELECT id, name " " FROM tbl_spaces " " WHERE parent_space_id = %s " " ORDER BY id ", (space['id'], )) rows_child_spaces = cursor_system.fetchall() if rows_child_spaces is not None and len(rows_child_spaces) > 0: for row in rows_child_spaces: child_space_list.append({"id": row[0], "name": row[1]}) ################################################################################################################ # Step 7: query base period energy cost ################################################################################################################ base = dict() if energy_category_set is not None and len(energy_category_set) > 0: for energy_category_id in energy_category_set: base[energy_category_id] = dict() base[energy_category_id]['timestamps'] = list() base[energy_category_id]['values'] = list() base[energy_category_id]['subtotal'] = Decimal(0.0) cursor_billing.execute( " SELECT start_datetime_utc, actual_value " " FROM tbl_space_input_category_hourly " " WHERE space_id = %s " " AND energy_category_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s " " ORDER BY start_datetime_utc ", (space['id'], energy_category_id, base_start_datetime_utc, base_end_datetime_utc)) rows_space_hourly = cursor_billing.fetchall() rows_space_periodically = utilities.aggregate_hourly_data_by_period( rows_space_hourly, base_start_datetime_utc, base_end_datetime_utc, period_type) for row_space_periodically in rows_space_periodically: current_datetime_local = row_space_periodically[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) if period_type == 'hourly': current_datetime = current_datetime_local.strftime( '%Y-%m-%dT%H:%M:%S') elif period_type == 'daily': current_datetime = current_datetime_local.strftime( '%Y-%m-%d') elif period_type == 'monthly': current_datetime = current_datetime_local.strftime( '%Y-%m') elif period_type == 'yearly': current_datetime = current_datetime_local.strftime( '%Y') actual_value = Decimal(0.0) if row_space_periodically[ 1] is None else row_space_periodically[1] base[energy_category_id]['timestamps'].append( current_datetime) base[energy_category_id]['values'].append(actual_value) base[energy_category_id]['subtotal'] += actual_value ################################################################################################################ # Step 8: query reporting period energy cost ################################################################################################################ reporting = dict() if energy_category_set is not None and len(energy_category_set) > 0: for energy_category_id in energy_category_set: reporting[energy_category_id] = dict() reporting[energy_category_id]['timestamps'] = list() reporting[energy_category_id]['values'] = list() reporting[energy_category_id]['subtotal'] = Decimal(0.0) reporting[energy_category_id]['toppeak'] = Decimal(0.0) reporting[energy_category_id]['onpeak'] = Decimal(0.0) reporting[energy_category_id]['midpeak'] = Decimal(0.0) reporting[energy_category_id]['offpeak'] = Decimal(0.0) cursor_billing.execute( " SELECT start_datetime_utc, actual_value " " FROM tbl_space_input_category_hourly " " WHERE space_id = %s " " AND energy_category_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s " " ORDER BY start_datetime_utc ", (space['id'], energy_category_id, reporting_start_datetime_utc, reporting_end_datetime_utc)) rows_space_hourly = cursor_billing.fetchall() rows_space_periodically = utilities.aggregate_hourly_data_by_period( rows_space_hourly, reporting_start_datetime_utc, reporting_end_datetime_utc, period_type) for row_space_periodically in rows_space_periodically: current_datetime_local = row_space_periodically[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) if period_type == 'hourly': current_datetime = current_datetime_local.strftime( '%Y-%m-%dT%H:%M:%S') elif period_type == 'daily': current_datetime = current_datetime_local.strftime( '%Y-%m-%d') elif period_type == 'monthly': current_datetime = current_datetime_local.strftime( '%Y-%m') elif period_type == 'yearly': current_datetime = current_datetime_local.strftime( '%Y') actual_value = Decimal(0.0) if row_space_periodically[ 1] is None else row_space_periodically[1] reporting[energy_category_id]['timestamps'].append( current_datetime) reporting[energy_category_id]['values'].append( actual_value) reporting[energy_category_id]['subtotal'] += actual_value energy_category_tariff_dict = utilities.get_energy_category_peak_types( space['cost_center_id'], energy_category_id, reporting_start_datetime_utc, reporting_end_datetime_utc) for row in rows_space_hourly: peak_type = energy_category_tariff_dict.get(row[0], None) if peak_type == 'toppeak': reporting[energy_category_id]['toppeak'] += row[1] elif peak_type == 'onpeak': reporting[energy_category_id]['onpeak'] += row[1] elif peak_type == 'midpeak': reporting[energy_category_id]['midpeak'] += row[1] elif peak_type == 'offpeak': reporting[energy_category_id]['offpeak'] += row[1] ################################################################################################################ # Step 9: query tariff data ################################################################################################################ parameters_data = dict() parameters_data['names'] = list() parameters_data['timestamps'] = list() parameters_data['values'] = list() if energy_category_set is not None and len(energy_category_set) > 0: for energy_category_id in energy_category_set: energy_category_tariff_dict = utilities.get_energy_category_tariffs( space['cost_center_id'], energy_category_id, reporting_start_datetime_utc, reporting_end_datetime_utc) tariff_timestamp_list = list() tariff_value_list = list() for k, v in energy_category_tariff_dict.items(): # convert k from utc to local k = k + timedelta(minutes=timezone_offset) tariff_timestamp_list.append(k.isoformat()[0:19][0:19]) tariff_value_list.append(v) parameters_data['names'].append( 'TARIFF-' + energy_category_dict[energy_category_id]['name']) parameters_data['timestamps'].append(tariff_timestamp_list) parameters_data['values'].append(tariff_value_list) ################################################################################################################ # Step 10: query associated sensors and points data ################################################################################################################ for point in point_list: point_values = [] point_timestamps = [] if point['object_type'] == 'ANALOG_VALUE': query = (" SELECT utc_date_time, actual_value " " FROM tbl_analog_value " " WHERE point_id = %s " " AND utc_date_time BETWEEN %s AND %s " " ORDER BY utc_date_time ") cursor_historical.execute( query, (point['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) rows = cursor_historical.fetchall() if rows is not None and len(rows) > 0: for row in rows: current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) current_datetime = current_datetime_local.strftime( '%Y-%m-%dT%H:%M:%S') point_timestamps.append(current_datetime) point_values.append(row[1]) elif point['object_type'] == 'ENERGY_VALUE': query = (" SELECT utc_date_time, actual_value " " FROM tbl_energy_value " " WHERE point_id = %s " " AND utc_date_time BETWEEN %s AND %s " " ORDER BY utc_date_time ") cursor_historical.execute( query, (point['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) rows = cursor_historical.fetchall() if rows is not None and len(rows) > 0: for row in rows: current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) current_datetime = current_datetime_local.strftime( '%Y-%m-%dT%H:%M:%S') point_timestamps.append(current_datetime) point_values.append(row[1]) elif point['object_type'] == 'DIGITAL_VALUE': query = (" SELECT utc_date_time, actual_value " " FROM tbl_digital_value " " WHERE point_id = %s " " AND utc_date_time BETWEEN %s AND %s ") cursor_historical.execute( query, (point['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) rows = cursor_historical.fetchall() if rows is not None and len(rows) > 0: for row in rows: current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) current_datetime = current_datetime_local.strftime( '%Y-%m-%dT%H:%M:%S') point_timestamps.append(current_datetime) point_values.append(row[1]) parameters_data['names'].append(point['name'] + ' (' + point['units'] + ')') parameters_data['timestamps'].append(point_timestamps) parameters_data['values'].append(point_values) ################################################################################################################ # Step 11: query child spaces energy cost ################################################################################################################ child_space_data = dict() if energy_category_set is not None and len(energy_category_set) > 0: for energy_category_id in energy_category_set: child_space_data[energy_category_id] = dict() child_space_data[energy_category_id][ 'child_space_names'] = list() child_space_data[energy_category_id]['subtotals'] = list() for child_space in child_space_list: child_space_data[energy_category_id][ 'child_space_names'].append(child_space['name']) cursor_billing.execute( " SELECT SUM(actual_value) " " FROM tbl_space_input_category_hourly " " WHERE space_id = %s " " AND energy_category_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s " " ORDER BY start_datetime_utc ", (child_space['id'], energy_category_id, reporting_start_datetime_utc, reporting_end_datetime_utc)) row_subtotal = cursor_billing.fetchone() subtotal = Decimal(0.0) if ( row_subtotal is None or row_subtotal[0] is None) else row_subtotal[0] child_space_data[energy_category_id]['subtotals'].append( subtotal) ################################################################################################################ # Step 12: construct the report ################################################################################################################ if cursor_system: cursor_system.close() if cnx_system: cnx_system.disconnect() if cursor_billing: cursor_billing.close() if cnx_billing: cnx_billing.disconnect() result = dict() result['space'] = dict() result['space']['name'] = space['name'] result['space']['area'] = space['area'] result['base_period'] = dict() result['base_period']['names'] = list() result['base_period']['units'] = list() result['base_period']['timestamps'] = list() result['base_period']['values'] = list() result['base_period']['subtotals'] = list() result['base_period']['total'] = Decimal(0.0) if energy_category_set is not None and len(energy_category_set) > 0: for energy_category_id in energy_category_set: result['base_period']['names'].append( energy_category_dict[energy_category_id]['name']) result['base_period']['units'].append(config.currency_unit) result['base_period']['timestamps'].append( base[energy_category_id]['timestamps']) result['base_period']['values'].append( base[energy_category_id]['values']) result['base_period']['subtotals'].append( base[energy_category_id]['subtotal']) result['base_period']['total'] += base[energy_category_id][ 'subtotal'] result['reporting_period'] = dict() result['reporting_period']['names'] = list() result['reporting_period']['energy_category_ids'] = list() result['reporting_period']['units'] = list() result['reporting_period']['timestamps'] = list() result['reporting_period']['values'] = list() result['reporting_period']['subtotals'] = list() result['reporting_period']['subtotals_per_unit_area'] = list() result['reporting_period']['toppeaks'] = list() result['reporting_period']['onpeaks'] = list() result['reporting_period']['midpeaks'] = list() result['reporting_period']['offpeaks'] = list() result['reporting_period']['increment_rates'] = list() result['reporting_period']['total'] = Decimal(0.0) result['reporting_period']['total_per_unit_area'] = Decimal(0.0) result['reporting_period']['total_increment_rate'] = Decimal(0.0) result['reporting_period']['total_unit'] = config.currency_unit if energy_category_set is not None and len(energy_category_set) > 0: for energy_category_id in energy_category_set: result['reporting_period']['names'].append( energy_category_dict[energy_category_id]['name']) result['reporting_period']['energy_category_ids'].append( energy_category_id) result['reporting_period']['units'].append( config.currency_unit) result['reporting_period']['timestamps'].append( reporting[energy_category_id]['timestamps']) result['reporting_period']['values'].append( reporting[energy_category_id]['values']) result['reporting_period']['subtotals'].append( reporting[energy_category_id]['subtotal']) result['reporting_period']['subtotals_per_unit_area'].append( reporting[energy_category_id]['subtotal'] / space['area'] if space['area'] > 0.0 else None) result['reporting_period']['toppeaks'].append( reporting[energy_category_id]['toppeak']) result['reporting_period']['onpeaks'].append( reporting[energy_category_id]['onpeak']) result['reporting_period']['midpeaks'].append( reporting[energy_category_id]['midpeak']) result['reporting_period']['offpeaks'].append( reporting[energy_category_id]['offpeak']) result['reporting_period']['increment_rates'].append( (reporting[energy_category_id]['subtotal'] - base[energy_category_id]['subtotal']) / base[energy_category_id]['subtotal'] if base[energy_category_id]['subtotal'] > 0.0 else None) result['reporting_period']['total'] += reporting[ energy_category_id]['subtotal'] result['reporting_period']['total_per_unit_area'] = \ result['reporting_period']['total'] / space['area'] if space['area'] > 0.0 else None result['reporting_period']['total_increment_rate'] = \ (result['reporting_period']['total'] - result['base_period']['total']) / \ result['base_period']['total'] \ if result['base_period']['total'] > Decimal(0.0) else None result['parameters'] = { "names": parameters_data['names'], "timestamps": parameters_data['timestamps'], "values": parameters_data['values'] } result['child_space'] = dict() result['child_space']['energy_category_names'] = list( ) # 1D array [energy category] result['child_space']['units'] = list() # 1D array [energy category] result['child_space']['child_space_names_array'] = list( ) # 2D array [energy category][child space] result['child_space']['subtotals_array'] = list( ) # 2D array [energy category][child space] result['child_space']['total_unit'] = config.currency_unit if energy_category_set is not None and len(energy_category_set) > 0: for energy_category_id in energy_category_set: result['child_space']['energy_category_names'].append( energy_category_dict[energy_category_id]['name']) result['child_space']['units'].append(config.currency_unit) result['child_space']['child_space_names_array'].append( child_space_data[energy_category_id]['child_space_names']) result['child_space']['subtotals_array'].append( child_space_data[energy_category_id]['subtotals']) # export result to Excel file and then encode the file to base64 string result['excel_bytes_base64'] = excelexporters.spacecost.export( result, space['name'], reporting_start_datetime_local, reporting_end_datetime_local, period_type) resp.body = json.dumps(result)
def on_get(req, resp): print(req.params) # this procedure accepts meter id or meter uuid to identify a meter meter_id = req.params.get('meterid') meter_uuid = req.params.get('meteruuid') period_type = req.params.get('periodtype') base_period_start_datetime = req.params.get('baseperiodstartdatetime') base_period_end_datetime = req.params.get('baseperiodenddatetime') reporting_period_start_datetime_local = req.params.get( 'reportingperiodstartdatetime') reporting_period_end_datetime_local = req.params.get( 'reportingperiodenddatetime') ################################################################################################################ # Step 1: valid parameters ################################################################################################################ if meter_id is None and meter_uuid is None: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_METER_ID') if meter_id is not None: meter_id = str.strip(meter_id) if not meter_id.isdigit() or int(meter_id) <= 0: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_METER_ID') if meter_uuid is not None: regex = re.compile( '^[a-f0-9]{8}-?[a-f0-9]{4}-?4[a-f0-9]{3}-?[89ab][a-f0-9]{3}-?[a-f0-9]{12}\Z', re.I) match = regex.match(str.strip(meter_uuid)) if not bool(match): raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_METER_UUID') if period_type is None: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_PERIOD_TYPE') else: period_type = str.strip(period_type) if period_type not in [ 'hourly', 'daily', 'weekly', 'monthly', 'yearly' ]: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_PERIOD_TYPE') timezone_offset = int(config.utc_offset[1:3]) * 60 + int( config.utc_offset[4:6]) if config.utc_offset[0] == '-': timezone_offset = -timezone_offset base_start_datetime_utc = None if base_period_start_datetime is not None and len( str.strip(base_period_start_datetime)) > 0: base_period_start_datetime = str.strip(base_period_start_datetime) try: base_start_datetime_utc = datetime.strptime( base_period_start_datetime, '%Y-%m-%dT%H:%M:%S') except ValueError: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_BASE_PERIOD_START_DATETIME") base_start_datetime_utc = base_start_datetime_utc.replace(tzinfo=timezone.utc) - \ timedelta(minutes=timezone_offset) base_end_datetime_utc = None if base_period_end_datetime is not None and len( str.strip(base_period_end_datetime)) > 0: base_period_end_datetime = str.strip(base_period_end_datetime) try: base_end_datetime_utc = datetime.strptime( base_period_end_datetime, '%Y-%m-%dT%H:%M:%S') except ValueError: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_BASE_PERIOD_END_DATETIME") base_end_datetime_utc = base_end_datetime_utc.replace(tzinfo=timezone.utc) - \ timedelta(minutes=timezone_offset) if base_start_datetime_utc is not None and base_end_datetime_utc is not None and \ base_start_datetime_utc >= base_end_datetime_utc: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_BASE_PERIOD_END_DATETIME') if reporting_period_start_datetime_local is None: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_REPORTING_PERIOD_START_DATETIME") else: reporting_period_start_datetime_local = str.strip( reporting_period_start_datetime_local) try: reporting_start_datetime_utc = datetime.strptime( reporting_period_start_datetime_local, '%Y-%m-%dT%H:%M:%S') except ValueError: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_REPORTING_PERIOD_START_DATETIME") reporting_start_datetime_utc = reporting_start_datetime_utc.replace(tzinfo=timezone.utc) - \ timedelta(minutes=timezone_offset) if reporting_period_end_datetime_local is None: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_REPORTING_PERIOD_END_DATETIME") else: reporting_period_end_datetime_local = str.strip( reporting_period_end_datetime_local) try: reporting_end_datetime_utc = datetime.strptime( reporting_period_end_datetime_local, '%Y-%m-%dT%H:%M:%S') except ValueError: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description="API.INVALID_REPORTING_PERIOD_END_DATETIME") reporting_end_datetime_utc = reporting_end_datetime_utc.replace(tzinfo=timezone.utc) - \ timedelta(minutes=timezone_offset) if reporting_start_datetime_utc >= reporting_end_datetime_utc: raise falcon.HTTPError( falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_REPORTING_PERIOD_END_DATETIME') ################################################################################################################ # Step 2: query the meter and energy category ################################################################################################################ cnx_system = mysql.connector.connect(**config.myems_system_db) cursor_system = cnx_system.cursor() cnx_energy = mysql.connector.connect(**config.myems_energy_db) cursor_energy = cnx_energy.cursor() cnx_historical = mysql.connector.connect(**config.myems_historical_db) cursor_historical = cnx_historical.cursor() if meter_id is not None: cursor_system.execute( " SELECT m.id, m.name, m.cost_center_id, m.energy_category_id, " " ec.name, ec.unit_of_measure, ec.kgce, ec.kgco2e " " FROM tbl_meters m, tbl_energy_categories ec " " WHERE m.id = %s AND m.energy_category_id = ec.id ", (meter_id, )) row_meter = cursor_system.fetchone() elif meter_uuid is not None: cursor_system.execute( " SELECT m.id, m.name, m.cost_center_id, m.energy_category_id, " " ec.name, ec.unit_of_measure, ec.kgce, ec.kgco2e " " FROM tbl_meters m, tbl_energy_categories ec " " WHERE m.uuid = %s AND m.energy_category_id = ec.id ", (meter_uuid, )) row_meter = cursor_system.fetchone() if row_meter is None: if cursor_system: cursor_system.close() if cnx_system: cnx_system.close() if cursor_energy: cursor_energy.close() if cnx_energy: cnx_energy.close() if cursor_historical: cursor_historical.close() if cnx_historical: cnx_historical.close() raise falcon.HTTPError(falcon.HTTP_404, title='API.NOT_FOUND', description='API.METER_NOT_FOUND') meter = dict() meter['id'] = row_meter[0] meter['name'] = row_meter[1] meter['cost_center_id'] = row_meter[2] meter['energy_category_id'] = row_meter[3] meter['energy_category_name'] = row_meter[4] meter['unit_of_measure'] = row_meter[5] meter['kgce'] = row_meter[6] meter['kgco2e'] = row_meter[7] ################################################################################################################ # Step 3: query associated points ################################################################################################################ point_list = list() cursor_system.execute( " SELECT p.id, p.name, p.units, p.object_type " " FROM tbl_meters m, tbl_meters_points mp, tbl_points p " " WHERE m.id = %s AND m.id = mp.meter_id AND mp.point_id = p.id " " ORDER BY p.id ", (meter['id'], )) rows_points = cursor_system.fetchall() if rows_points is not None and len(rows_points) > 0: for row in rows_points: point_list.append({ "id": row[0], "name": row[1], "units": row[2], "object_type": row[3] }) ################################################################################################################ # Step 4: query base period energy consumption ################################################################################################################ cnx_energy = mysql.connector.connect(**config.myems_energy_db) cursor_energy = cnx_energy.cursor() query = (" SELECT start_datetime_utc, actual_value " " FROM tbl_meter_hourly " " WHERE meter_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s " " ORDER BY start_datetime_utc ") cursor_energy.execute( query, (meter['id'], base_start_datetime_utc, base_end_datetime_utc)) rows_meter_hourly = cursor_energy.fetchall() rows_meter_periodically = utilities.aggregate_hourly_data_by_period( rows_meter_hourly, base_start_datetime_utc, base_end_datetime_utc, period_type) base = dict() base['timestamps'] = list() base['values'] = list() base['total_in_category'] = Decimal(0.0) base['total_in_kgce'] = Decimal(0.0) base['total_in_kgco2e'] = Decimal(0.0) for row_meter_periodically in rows_meter_periodically: current_datetime_local = row_meter_periodically[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) if period_type == 'hourly': current_datetime = current_datetime_local.strftime( '%Y-%m-%dT%H:%M:%S') elif period_type == 'daily': current_datetime = current_datetime_local.strftime('%Y-%m-%d') elif period_type == 'weekly': current_datetime = current_datetime_local.strftime('%Y-%m-%d') elif period_type == 'monthly': current_datetime = current_datetime_local.strftime('%Y-%m') elif period_type == 'yearly': current_datetime = current_datetime_local.strftime('%Y') actual_value = Decimal(0.0) if row_meter_periodically[ 1] is None else row_meter_periodically[1] base['timestamps'].append(current_datetime) base['values'].append(actual_value) base['total_in_category'] += actual_value base['total_in_kgce'] += actual_value * meter['kgce'] base['total_in_kgco2e'] += actual_value * meter['kgco2e'] ################################################################################################################ # Step 5: query reporting period energy consumption ################################################################################################################ query = (" SELECT start_datetime_utc, actual_value " " FROM tbl_meter_hourly " " WHERE meter_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s " " ORDER BY start_datetime_utc ") cursor_energy.execute(query, (meter['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) rows_meter_hourly = cursor_energy.fetchall() rows_meter_periodically = utilities.aggregate_hourly_data_by_period( rows_meter_hourly, reporting_start_datetime_utc, reporting_end_datetime_utc, period_type) reporting = dict() reporting['timestamps'] = list() reporting['values'] = list() reporting['total_in_category'] = Decimal(0.0) reporting['total_in_kgce'] = Decimal(0.0) reporting['total_in_kgco2e'] = Decimal(0.0) for row_meter_periodically in rows_meter_periodically: current_datetime_local = row_meter_periodically[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) if period_type == 'hourly': current_datetime = current_datetime_local.strftime( '%Y-%m-%dT%H:%M:%S') elif period_type == 'daily': current_datetime = current_datetime_local.strftime('%Y-%m-%d') elif period_type == 'weekly': current_datetime = current_datetime_local.strftime('%Y-%m-%d') elif period_type == 'monthly': current_datetime = current_datetime_local.strftime('%Y-%m') elif period_type == 'yearly': current_datetime = current_datetime_local.strftime('%Y') actual_value = Decimal(0.0) if row_meter_periodically[ 1] is None else row_meter_periodically[1] reporting['timestamps'].append(current_datetime) reporting['values'].append(actual_value) reporting['total_in_category'] += actual_value reporting['total_in_kgce'] += actual_value * meter['kgce'] reporting['total_in_kgco2e'] += actual_value * meter['kgco2e'] ################################################################################################################ # Step 6: query tariff data ################################################################################################################ parameters_data = dict() parameters_data['names'] = list() parameters_data['timestamps'] = list() parameters_data['values'] = list() tariff_dict = utilities.get_energy_category_tariffs( meter['cost_center_id'], meter['energy_category_id'], reporting_start_datetime_utc, reporting_end_datetime_utc) print(tariff_dict) tariff_timestamp_list = list() tariff_value_list = list() for k, v in tariff_dict.items(): # convert k from utc to local k = k + timedelta(minutes=timezone_offset) tariff_timestamp_list.append(k.isoformat()[0:19]) tariff_value_list.append(v) parameters_data['names'].append('TARIFF-' + meter['energy_category_name']) parameters_data['timestamps'].append(tariff_timestamp_list) parameters_data['values'].append(tariff_value_list) ################################################################################################################ # Step 7: query associated points data ################################################################################################################ for point in point_list: point_values = [] point_timestamps = [] if point['object_type'] == 'ANALOG_VALUE': query = (" SELECT utc_date_time, actual_value " " FROM tbl_analog_value " " WHERE point_id = %s " " AND utc_date_time BETWEEN %s AND %s " " ORDER BY utc_date_time ") cursor_historical.execute( query, (point['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) rows = cursor_historical.fetchall() if rows is not None and len(rows) > 0: for row in rows: current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) current_datetime = current_datetime_local.strftime( '%Y-%m-%dT%H:%M:%S') point_timestamps.append(current_datetime) point_values.append(row[1]) elif point['object_type'] == 'ENERGY_VALUE': query = (" SELECT utc_date_time, actual_value " " FROM tbl_energy_value " " WHERE point_id = %s " " AND utc_date_time BETWEEN %s AND %s " " ORDER BY utc_date_time ") cursor_historical.execute( query, (point['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) rows = cursor_historical.fetchall() if rows is not None and len(rows) > 0: for row in rows: current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) current_datetime = current_datetime_local.strftime( '%Y-%m-%dT%H:%M:%S') point_timestamps.append(current_datetime) point_values.append(row[1]) elif point['object_type'] == 'DIGITAL_VALUE': query = (" SELECT utc_date_time, actual_value " " FROM tbl_digital_value " " WHERE point_id = %s " " AND utc_date_time BETWEEN %s AND %s " " ORDER BY utc_date_time ") cursor_historical.execute( query, (point['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) rows = cursor_historical.fetchall() if rows is not None and len(rows) > 0: for row in rows: current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ timedelta(minutes=timezone_offset) current_datetime = current_datetime_local.strftime( '%Y-%m-%dT%H:%M:%S') point_timestamps.append(current_datetime) point_values.append(row[1]) parameters_data['names'].append(point['name'] + ' (' + point['units'] + ')') parameters_data['timestamps'].append(point_timestamps) parameters_data['values'].append(point_values) ################################################################################################################ # Step 8: construct the report ################################################################################################################ if cursor_system: cursor_system.close() if cnx_system: cnx_system.close() if cursor_energy: cursor_energy.close() if cnx_energy: cnx_energy.close() if cursor_historical: cursor_historical.close() if cnx_historical: cnx_historical.close() result = { "meter": { "cost_center_id": meter['cost_center_id'], "energy_category_id": meter['energy_category_id'], "energy_category_name": meter['energy_category_name'], "unit_of_measure": meter['unit_of_measure'], "kgce": meter['kgce'], "kgco2e": meter['kgco2e'], }, "base_period": { "total_in_category": base['total_in_category'], "total_in_kgce": base['total_in_kgce'], "total_in_kgco2e": base['total_in_kgco2e'], "timestamps": base['timestamps'], "values": base['values'] }, "reporting_period": { "increment_rate": (reporting['total_in_category'] - base['total_in_category']) / base['total_in_category'] if base['total_in_category'] > 0 else None, "total_in_category": reporting['total_in_category'], "total_in_kgce": reporting['total_in_kgce'], "total_in_kgco2e": reporting['total_in_kgco2e'], "timestamps": reporting['timestamps'], "values": reporting['values'], }, "parameters": { "names": parameters_data['names'], "timestamps": parameters_data['timestamps'], "values": parameters_data['values'] }, } # export result to Excel file and then encode the file to base64 string result['excel_bytes_base64'] = \ excelexporters.meterenergy.export(result, meter['name'], reporting_period_start_datetime_local, reporting_period_end_datetime_local, period_type) resp.text = json.dumps(result)