import falcon import simplejson as json import mysql.connector import config from datetime import datetime, timedelta, timezone from core import utilities from decimal import Decimal import excelexporters.spacecost class Reporting: @staticmethod def __init__(): """Initializes Class""" pass @staticmethod def on_options(req, resp): resp.status = falcon.HTTP_200 #################################################################################################################### # PROCEDURES # Step 1: valid parameters # Step 2: query the space # Step 3: query energy categories # Step 4: query associated sensors # Step 5: query associated points # Step 6: query child spaces # Step 7: query base period energy cost # Step 8: query reporting period energy cost # Step 9: query tariff data # Step 10: query associated sensors and points data # Step 11: query child spaces energy cost # Step 12: construct the report #################################################################################################################### @staticmethod 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', '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 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 cursor_historical: cursor_historical.close() if cnx_historical: cnx_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 cursor_historical: cursor_historical.close() if cnx_historical: cnx_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 == '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_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 == '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_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 " " 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 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() if cursor_historical: cursor_historical.close() if cnx_historical: cnx_historical.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.text = json.dumps(result)