import re 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.storeenergyitem 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 store # Step 3: query energy items # Step 4: query associated sensors # Step 5: query associated points # Step 6: query base period energy input # Step 7: query reporting period energy input # Step 8: query tariff data # Step 9: query associated sensors and points data # Step 10: construct the report #################################################################################################################### @staticmethod def on_get(req, resp): print(req.params) store_id = req.params.get('storeid') store_uuid = req.params.get('storeuuid') 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 store_id is None and store_uuid is None: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_STORE_ID') if store_id is not None: store_id = str.strip(store_id) if not store_id.isdigit() or int(store_id) <= 0: raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_STORE_ID') if store_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(store_uuid)) if not bool(match): raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_STORE_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 store ################################################################################################################ 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 store_id is not None: cursor_system.execute(" SELECT id, name, area, cost_center_id " " FROM tbl_stores " " WHERE id = %s ", (store_id,)) row_store = cursor_system.fetchone() elif store_uuid is not None: cursor_system.execute(" SELECT id, name, area, cost_center_id " " FROM tbl_stores " " WHERE uuid = %s ", (store_uuid,)) row_store = cursor_system.fetchone() if row_store 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.STORE_NOT_FOUND') store = dict() store['id'] = row_store[0] store['name'] = row_store[1] store['area'] = row_store[2] store['cost_center_id'] = row_store[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_store_input_item_hourly " " WHERE store_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s ", (store['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_store_input_item_hourly " " WHERE store_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s ", (store['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.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_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_stores st, tbl_sensors se, tbl_stores_sensors ss, " " tbl_points p, tbl_sensors_points sp " " WHERE st.id = %s AND st.id = ss.store_id AND ss.sensor_id = se.id " " AND se.id = sp.sensor_id AND sp.point_id = p.id " " ORDER BY p.id ", (store['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_stores s, tbl_stores_points sp, tbl_points p " " WHERE s.id = %s AND s.id = sp.store_id AND sp.point_id = p.id " " ORDER BY p.id ", (store['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_store_input_item_hourly " " WHERE store_id = %s " " AND energy_item_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s " " ORDER BY start_datetime_utc ", (store['id'], energy_item_id, base_start_datetime_utc, base_end_datetime_utc)) rows_store_hourly = cursor_energy.fetchall() rows_store_periodically = utilities.aggregate_hourly_data_by_period(rows_store_hourly, base_start_datetime_utc, base_end_datetime_utc, period_type) for row_store_periodically in rows_store_periodically: current_datetime_local = row_store_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_store_periodically[1] is None else row_store_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_store_input_item_hourly " " WHERE store_id = %s " " AND energy_item_id = %s " " AND start_datetime_utc >= %s " " AND start_datetime_utc < %s " " ORDER BY start_datetime_utc ", (store['id'], energy_item_id, reporting_start_datetime_utc, reporting_end_datetime_utc)) rows_store_hourly = cursor_energy.fetchall() rows_store_periodically = utilities.aggregate_hourly_data_by_period(rows_store_hourly, reporting_start_datetime_utc, reporting_end_datetime_utc, period_type) for row_store_periodically in rows_store_periodically: current_datetime_local = row_store_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_store_periodically[1] is None else row_store_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(store['cost_center_id'], energy_item_dict[energy_item_id]['energy_category_id'], reporting_start_datetime_utc, reporting_end_datetime_utc) for row in rows_store_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(store['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 " " 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: 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['store'] = dict() result['store']['name'] = store['name'] result['store']['area'] = store['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'] / store['area'] if store['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'] } # export result to Excel file and then encode the file to base64 string result['excel_bytes_base64'] = excelexporters.storeenergyitem.export(result, store['name'], reporting_start_datetime_local, reporting_end_datetime_local, period_type) resp.text = json.dumps(result)