myems-api/reports/shopfloordashboard.py
from datetime import datetime, timedelta, timezone
from decimal import Decimal
import falcon
import mysql.connector
import simplejson as json
import config
from core import utilities
from core.useractivity import access_control, api_key_control
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 sensor data
# Step 5: query child spaces
# Step 6: query base period energy input
# Step 7: query base period energy cost
# Step 8: query reporting period energy input
# Step 9: query reporting period energy cost
# Step 10: query child spaces energy input
# Step 10: query child spaces energy cost
# Step 12: construct the report
####################################################################################################################
@staticmethod
def on_get(req, resp):
# todo: change this procedure from space to shopfloor
if 'API-KEY' not in req.headers or \
not isinstance(req.headers['API-KEY'], str) or \
len(str.strip(req.headers['API-KEY'])) == 0:
access_control(req)
else:
api_key_control(req)
user_uuid = req.params.get('useruuid')
period_type = req.params.get('periodtype')
base_period_start_datetime_local = req.params.get('baseperiodstartdatetime')
base_period_end_datetime_local = 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 user_uuid is None:
raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_USER_UUID')
else:
user_uuid = str.strip(user_uuid)
if len(user_uuid) != 36:
raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST',
description='API.INVALID_USER_UUID')
if period_type is None:
raise falcon.HTTPError(status=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(status=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_local is not None and len(str.strip(base_period_start_datetime_local)) > 0:
base_period_start_datetime_local = str.strip(base_period_start_datetime_local)
try:
base_start_datetime_utc = datetime.strptime(base_period_start_datetime_local, '%Y-%m-%dT%H:%M:%S')
except ValueError:
raise falcon.HTTPError(status=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)
# nomalize the start datetime
if config.minutes_to_count == 30 and base_start_datetime_utc.minute >= 30:
base_start_datetime_utc = base_start_datetime_utc.replace(minute=30, second=0, microsecond=0)
else:
base_start_datetime_utc = base_start_datetime_utc.replace(minute=0, second=0, microsecond=0)
base_end_datetime_utc = None
if base_period_end_datetime_local is not None and len(str.strip(base_period_end_datetime_local)) > 0:
base_period_end_datetime_local = str.strip(base_period_end_datetime_local)
try:
base_end_datetime_utc = datetime.strptime(base_period_end_datetime_local, '%Y-%m-%dT%H:%M:%S')
except ValueError:
raise falcon.HTTPError(status=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(status=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(status=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(status=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)
# nomalize the start datetime
if config.minutes_to_count == 30 and reporting_start_datetime_utc.minute >= 30:
reporting_start_datetime_utc = reporting_start_datetime_utc.replace(minute=30, second=0, microsecond=0)
else:
reporting_start_datetime_utc = reporting_start_datetime_utc.replace(minute=0, second=0, microsecond=0)
if reporting_period_end_datetime_local is None:
raise falcon.HTTPError(status=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').replace(tzinfo=timezone.utc) - \
timedelta(minutes=timezone_offset)
except ValueError:
raise falcon.HTTPError(status=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(status=falcon.HTTP_400, title='API.BAD_REQUEST',
description='API.INVALID_REPORTING_PERIOD_END_DATETIME')
################################################################################################################
# Step 2: query the space
################################################################################################################
cnx_user = mysql.connector.connect(**config.myems_user_db)
cursor_user = cnx_user.cursor()
cursor_user.execute(" SELECT id, is_admin, privilege_id "
" FROM tbl_users "
" WHERE uuid = %s ", (user_uuid,))
row_user = cursor_user.fetchone()
if row_user is None:
if cursor_user:
cursor_user.close()
if cnx_user:
cnx_user.close()
raise falcon.HTTPError(status=falcon.HTTP_404, title='API.NOT_FOUND',
description='API.USER_NOT_FOUND')
user = {'id': row_user[0], 'is_admin': row_user[1], 'privilege_id': row_user[2]}
if user['is_admin']:
# todo: make sure the space id is always 1 for admin
space_id = 1
else:
cursor_user.execute(" SELECT data "
" FROM tbl_privileges "
" WHERE id = %s ", (user['privilege_id'],))
row_privilege = cursor_user.fetchone()
if row_privilege is None:
if cursor_user:
cursor_user.close()
if cnx_user:
cnx_user.close()
raise falcon.HTTPError(status=falcon.HTTP_404, title='API.NOT_FOUND',
description='API.USER_PRIVILEGE_NOT_FOUND')
privilege_data = json.loads(row_privilege[0])
if 'spaces' not in privilege_data.keys() \
or privilege_data['spaces'] is None \
or len(privilege_data['spaces']) == 0:
if cursor_user:
cursor_user.close()
if cnx_user:
cnx_user.close()
raise falcon.HTTPError(status=falcon.HTTP_404, title='API.NOT_FOUND',
description='API.USER_PRIVILEGE_NOT_FOUND')
# todo: how to deal with multiple spaces in privilege data
space_id = privilege_data['spaces'][0]
if cursor_user:
cursor_user.close()
if cnx_user:
cnx_user.close()
cnx_system = mysql.connector.connect(**config.myems_system_db)
cursor_system = cnx_system.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.close()
raise falcon.HTTPError(status=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
################################################################################################################
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()
energy_category_set = set()
# query energy categories in base period
cursor_energy.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_energy.fetchall()
if rows_energy_categories is not None and 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_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_energy.fetchall()
if rows_energy_categories is not None and 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_billing:
cursor_billing.close()
if cnx_billing:
cnx_billing.close()
raise falcon.HTTPError(status=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 sensor data
################################################################################################################
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()
sensor_id_list = list()
sensor_dict = dict()
cursor_system.execute(" SELECT s.id, s.name, s.uuid, s.description "
" FROM tbl_sensors s, tbl_spaces_sensors ss "
" WHERE ss.space_id = %s "
" AND s.id = ss.sensor_id "
, (space['id'],))
rows_sensors = cursor_system.fetchall()
if rows_sensors is not None and len(rows_sensors) > 0:
for row in rows_sensors:
sensor_id_list.append(row[0])
sensor_dict[row[0]] = dict()
sensor_dict[row[0]]['name'] = row[1]
sensor_dict[row[0]]['description'] = row[2]
sensor_dict[row[0]]['uuid'] = row[3]
sensor_dict[row[0]]['point_name_list'] = list()
sensor_dict[row[0]]['point_unit_list'] = list()
sensor_dict[row[0]]['point_id_list'] = list()
if sensor_id_list is not None and len(sensor_id_list) > 0:
cursor_system.execute(" SELECT sp.sensor_id, p.id, p.name, p.units "
" FROM tbl_sensors_points sp, tbl_points p "
" WHERE sp.sensor_id in ({}) "
" AND sp.point_id = p.id "
" ORDER BY p.id ".format(','.join("{0}".format(x) for x in sensor_id_list)))
rows_sensor_points = cursor_system.fetchall()
if rows_sensor_points is not None and len(rows_sensor_points) > 0:
for row in rows_sensor_points:
sensor_dict[row[0]]['point_id_list'].append(row[1])
sensor_dict[row[0]]['point_name_list'].append(row[2])
sensor_dict[row[0]]['point_unit_list'].append(row[3])
point_data_dict = dict()
for key in sensor_dict:
if sensor_dict[key]['point_id_list'] is not None and len(sensor_dict[key]['point_id_list']) > 0:
cursor_historical.execute(" SELECT point_id, actual_value "
" FROM tbl_analog_value_latest "
" WHERE point_id in ({}) "
" ORDER BY point_id ".
format(','.join("{0}".format(x) for x in sensor_dict[key]['point_id_list'])))
rows_analog_values = cursor_historical.fetchall()
if rows_analog_values is not None and len(rows_analog_values) > 0:
for row in rows_analog_values:
point_data_dict[row[0]] = row[1]
cursor_historical.execute(" SELECT point_id, actual_value "
" FROM tbl_digital_value_latest "
" WHERE point_id in ({}) "
" ORDER BY point_id ".
format(','.join("{0}".format(x) for x in sensor_dict[key]['point_id_list'])))
rows_digital_values = cursor_historical.fetchall()
if rows_digital_values is not None and len(rows_digital_values) > 0:
for row in rows_digital_values:
point_data_dict[row[0]] = row[1]
################################################################################################################
# Step 5: 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 6: query base period energy input
################################################################################################################
base_input = 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_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)
base_input[energy_category_id]['subtotal_in_kgce'] = Decimal(0.0)
base_input[energy_category_id]['subtotal_in_kgco2e'] = Decimal(0.0)
cursor_energy.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_energy.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_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
base_input[energy_category_id]['subtotal_in_kgce'] += actual_value * kgce
base_input[energy_category_id]['subtotal_in_kgco2e'] += actual_value * kgco2e
################################################################################################################
# Step 7: query base period energy cost
################################################################################################################
base_cost = dict()
if energy_category_set is not None and len(energy_category_set) > 0:
for energy_category_id in energy_category_set:
base_cost[energy_category_id] = dict()
base_cost[energy_category_id]['timestamps'] = list()
base_cost[energy_category_id]['values'] = list()
base_cost[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_cost[energy_category_id]['timestamps'].append(current_datetime)
base_cost[energy_category_id]['values'].append(actual_value)
base_cost[energy_category_id]['subtotal'] += actual_value
################################################################################################################
# Step 8: 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:
kgce = energy_category_dict[energy_category_id]['kgce']
kgco2e = energy_category_dict[energy_category_id]['kgco2e']
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)
reporting_input[energy_category_id]['subtotal_in_kgce'] = Decimal(0.0)
reporting_input[energy_category_id]['subtotal_in_kgco2e'] = Decimal(0.0)
reporting_input[energy_category_id]['toppeak'] = Decimal(0.0)
reporting_input[energy_category_id]['onpeak'] = Decimal(0.0)
reporting_input[energy_category_id]['midpeak'] = Decimal(0.0)
reporting_input[energy_category_id]['offpeak'] = Decimal(0.0)
cursor_energy.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_energy.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_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
reporting_input[energy_category_id]['subtotal_in_kgce'] += actual_value * kgce
reporting_input[energy_category_id]['subtotal_in_kgco2e'] += actual_value * kgco2e
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_input[energy_category_id]['toppeak'] += row[1]
elif peak_type == 'onpeak':
reporting_input[energy_category_id]['onpeak'] += row[1]
elif peak_type == 'midpeak':
reporting_input[energy_category_id]['midpeak'] += row[1]
elif peak_type == 'offpeak':
reporting_input[energy_category_id]['offpeak'] += row[1]
################################################################################################################
# Step 9: 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)
reporting_cost[energy_category_id]['toppeak'] = Decimal(0.0)
reporting_cost[energy_category_id]['onpeak'] = Decimal(0.0)
reporting_cost[energy_category_id]['midpeak'] = Decimal(0.0)
reporting_cost[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_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
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_cost[energy_category_id]['toppeak'] += row[1]
elif peak_type == 'onpeak':
reporting_cost[energy_category_id]['onpeak'] += row[1]
elif peak_type == 'midpeak':
reporting_cost[energy_category_id]['midpeak'] += row[1]
elif peak_type == 'offpeak':
reporting_cost[energy_category_id]['offpeak'] += row[1]
################################################################################################################
# Step 10: query child spaces energy input
################################################################################################################
child_space_input = dict()
if energy_category_set is not None and len(energy_category_set) > 0:
for energy_category_id in energy_category_set:
child_space_input[energy_category_id] = dict()
child_space_input[energy_category_id]['child_space_names'] = list()
child_space_input[energy_category_id]['subtotals'] = list()
child_space_input[energy_category_id]['subtotals_in_kgce'] = list()
child_space_input[energy_category_id]['subtotals_in_kgco2e'] = list()
kgce = energy_category_dict[energy_category_id]['kgce']
kgco2e = energy_category_dict[energy_category_id]['kgco2e']
for child_space in child_space_list:
child_space_input[energy_category_id]['child_space_names'].append(child_space['name'])
subtotal = 0
subtotal_list = list()
cursor_energy.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 ",
(child_space['id'],
energy_category_id,
reporting_start_datetime_utc,
reporting_end_datetime_utc))
row_subtotal = cursor_energy.fetchall()
rows_space_periodically = utilities.aggregate_hourly_data_by_period(row_subtotal,
reporting_start_datetime_utc,
reporting_end_datetime_utc,
period_type)
for row_space_periodically in rows_space_periodically:
actual_value = Decimal(0.0) if row_space_periodically[1] is None else row_space_periodically[1]
subtotal_list.append(actual_value)
subtotal += actual_value
child_space_input[energy_category_id]['subtotals'].append(subtotal_list)
child_space_input[energy_category_id]['subtotals_in_kgce'].append(subtotal * kgce)
child_space_input[energy_category_id]['subtotals_in_kgco2e'].append(subtotal * kgco2e)
################################################################################################################
# Step 10: query child spaces energy cost
################################################################################################################
child_space_cost = dict()
if energy_category_set is not None and len(energy_category_set) > 0:
for energy_category_id in energy_category_set:
child_space_cost[energy_category_id] = dict()
child_space_cost[energy_category_id]['child_space_names'] = list()
child_space_cost[energy_category_id]['subtotals'] = list()
for child_space in child_space_list:
child_space_cost[energy_category_id]['child_space_names'].append(child_space['name'])
subtotal_list = list()
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 ",
(child_space['id'],
energy_category_id,
reporting_start_datetime_utc,
reporting_end_datetime_utc))
row_subtotal = cursor_billing.fetchall()
rows_space_periodically = utilities.aggregate_hourly_data_by_period(row_subtotal,
reporting_start_datetime_utc,
reporting_end_datetime_utc,
period_type)
for row_space_periodically in rows_space_periodically:
actual_value = Decimal(0.0) if row_space_periodically[1] is None else row_space_periodically[1]
subtotal_list.append(actual_value)
child_space_cost[energy_category_id]['subtotals'].append(subtotal_list)
################################################################################################################
# Step 12: 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_billing:
cursor_billing.close()
if cnx_billing:
cnx_billing.close()
result = dict()
result['space'] = dict()
result['space']['name'] = space['name']
result['space']['area'] = space['area']
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()
result['base_period_input']['subtotals_in_kgce'] = list()
result['base_period_input']['subtotals_in_kgco2e'] = list()
result['base_period_input']['subtotals_per_unit_area'] = list()
result['base_period_input']['total_in_kgce'] = Decimal(0.0)
result['base_period_input']['total_in_kgco2e'] = 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_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_input']['subtotals_in_kgce'].append(
base_input[energy_category_id]['subtotal_in_kgce'])
result['base_period_input']['subtotals_in_kgco2e'].append(
base_input[energy_category_id]['subtotal_in_kgco2e'])
result['base_period_input']['subtotals_per_unit_area'].append(
base_input[energy_category_id]['subtotal'] / space['area']
if space['area'] > 0.0 else None)
result['base_period_input']['total_in_kgce'] += \
base_input[energy_category_id]['subtotal_in_kgce']
result['base_period_input']['total_in_kgco2e'] += \
base_input[energy_category_id]['subtotal_in_kgco2e']
result['sensor'] = dict()
result['point'] = dict()
result['sensor'] = sensor_dict
result['point'] = point_data_dict
result['base_period_cost'] = dict()
result['base_period_cost']['names'] = list()
result['base_period_cost']['units'] = list()
result['base_period_cost']['timestamps'] = list()
result['base_period_cost']['values'] = list()
result['base_period_cost']['subtotals'] = list()
result['base_period_cost']['subtotals_per_unit_area'] = list()
result['base_period_cost']['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_cost']['names'].append(
energy_category_dict[energy_category_id]['name'])
result['base_period_cost']['units'].append(config.currency_unit)
result['base_period_cost']['timestamps'].append(
base_cost[energy_category_id]['timestamps'])
result['base_period_cost']['values'].append(
base_cost[energy_category_id]['values'])
result['base_period_cost']['subtotals'].append(
base_cost[energy_category_id]['subtotal'])
result['base_period_cost']['subtotals_per_unit_area'].append(
base_cost[energy_category_id]['subtotal'] / space['area']
if space['area'] > 0.0 else None)
result['base_period_cost']['total'] += base_cost[energy_category_id]['subtotal']
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']['subtotals_in_kgce'] = list()
result['reporting_period_input']['subtotals_in_kgco2e'] = list()
result['reporting_period_input']['subtotals_per_unit_area'] = list()
result['reporting_period_input']['toppeaks'] = list()
result['reporting_period_input']['onpeaks'] = list()
result['reporting_period_input']['midpeaks'] = list()
result['reporting_period_input']['offpeaks'] = list()
result['reporting_period_input']['increment_rates'] = list()
result['reporting_period_input']['total_in_kgce'] = Decimal(0.0)
result['reporting_period_input']['total_in_kgco2e'] = Decimal(0.0)
result['reporting_period_input']['increment_rate_in_kgce'] = Decimal(0.0)
result['reporting_period_input']['increment_rate_in_kgco2e'] = 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_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']['subtotals_in_kgce'].append(
reporting_input[energy_category_id]['subtotal_in_kgce'])
result['reporting_period_input']['subtotals_in_kgco2e'].append(
reporting_input[energy_category_id]['subtotal_in_kgco2e'])
result['reporting_period_input']['subtotals_per_unit_area'].append(
reporting_input[energy_category_id]['subtotal'] / space['area']
if space['area'] > 0.0 else None)
result['reporting_period_input']['toppeaks'].append(
reporting_input[energy_category_id]['toppeak'])
result['reporting_period_input']['onpeaks'].append(
reporting_input[energy_category_id]['onpeak'])
result['reporting_period_input']['midpeaks'].append(
reporting_input[energy_category_id]['midpeak'])
result['reporting_period_input']['offpeaks'].append(
reporting_input[energy_category_id]['offpeak'])
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_input']['total_in_kgce'] += \
reporting_input[energy_category_id]['subtotal_in_kgce']
result['reporting_period_input']['total_in_kgco2e'] += \
reporting_input[energy_category_id]['subtotal_in_kgco2e']
result['reporting_period_input']['total_in_kgco2e_per_unit_area'] = \
result['reporting_period_input']['total_in_kgce'] / space['area'] if space['area'] > 0.0 else None
result['reporting_period_input']['increment_rate_in_kgce'] = \
(result['reporting_period_input']['total_in_kgce'] - result['base_period_input']['total_in_kgce']) / \
result['base_period_input']['total_in_kgce'] \
if result['base_period_input']['total_in_kgce'] > Decimal(0.0) else None
result['reporting_period_input']['total_in_kgce_per_unit_area'] = \
result['reporting_period_input']['total_in_kgco2e'] / space['area'] if space['area'] > 0.0 else None
result['reporting_period_input']['increment_rate_in_kgco2e'] = \
(result['reporting_period_input']['total_in_kgco2e'] - result['base_period_input']['total_in_kgco2e']) / \
result['base_period_input']['total_in_kgco2e'] \
if result['base_period_input']['total_in_kgco2e'] > Decimal(0.0) else None
result['reporting_period_cost'] = dict()
result['reporting_period_cost']['names'] = list()
result['reporting_period_cost']['energy_category_ids'] = list()
result['reporting_period_cost']['units'] = list()
result['reporting_period_cost']['timestamps'] = list()
result['reporting_period_cost']['values'] = list()
result['reporting_period_cost']['subtotals'] = list()
result['reporting_period_cost']['subtotals_per_unit_area'] = list()
result['reporting_period_cost']['toppeaks'] = list()
result['reporting_period_cost']['onpeaks'] = list()
result['reporting_period_cost']['midpeaks'] = list()
result['reporting_period_cost']['offpeaks'] = list()
result['reporting_period_cost']['increment_rates'] = list()
result['reporting_period_cost']['total'] = Decimal(0.0)
result['reporting_period_cost']['total_per_unit_area'] = Decimal(0.0)
result['reporting_period_cost']['total_increment_rate'] = Decimal(0.0)
result['reporting_period_cost']['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_cost']['names'].append(energy_category_dict[energy_category_id]['name'])
result['reporting_period_cost']['energy_category_ids'].append(energy_category_id)
result['reporting_period_cost']['units'].append(config.currency_unit)
result['reporting_period_cost']['timestamps'].append(
reporting_cost[energy_category_id]['timestamps'])
result['reporting_period_cost']['values'].append(
reporting_cost[energy_category_id]['values'])
result['reporting_period_cost']['subtotals'].append(
reporting_cost[energy_category_id]['subtotal'])
result['reporting_period_cost']['subtotals_per_unit_area'].append(
reporting_cost[energy_category_id]['subtotal'] / space['area']
if space['area'] > 0.0 else None)
result['reporting_period_cost']['toppeaks'].append(
reporting_cost[energy_category_id]['toppeak'])
result['reporting_period_cost']['onpeaks'].append(
reporting_cost[energy_category_id]['onpeak'])
result['reporting_period_cost']['midpeaks'].append(
reporting_cost[energy_category_id]['midpeak'])
result['reporting_period_cost']['offpeaks'].append(
reporting_cost[energy_category_id]['offpeak'])
result['reporting_period_cost']['increment_rates'].append(
(reporting_cost[energy_category_id]['subtotal'] -
base_cost[energy_category_id]['subtotal']) /
base_cost[energy_category_id]['subtotal']
if base_cost[energy_category_id]['subtotal'] > 0.0 else None)
result['reporting_period_cost']['total'] += reporting_cost[energy_category_id]['subtotal']
result['reporting_period_cost']['total_per_unit_area'] = \
result['reporting_period_cost']['total'] / space['area'] if space['area'] > 0.0 else None
result['reporting_period_cost']['total_increment_rate'] = \
(result['reporting_period_cost']['total'] - result['base_period_cost']['total']) / \
result['reporting_period_cost']['total'] \
if result['reporting_period_cost']['total'] > Decimal(0.0) else None
result['child_space_input'] = dict()
result['child_space_input']['energy_category_names'] = list() # 1D array [energy category]
result['child_space_input']['units'] = list() # 1D array [energy category]
result['child_space_input']['child_space_names_array'] = list() # 2D array [energy category][child space]
result['child_space_input']['subtotals_array'] = list() # 2D array [energy category][child space]
result['child_space_input']['subtotals_in_kgce_array'] = list() # 2D array [energy category][child space]
result['child_space_input']['subtotals_in_kgco2e_array'] = list() # 2D array [energy category][child space]
if energy_category_set is not None and len(energy_category_set) > 0:
for energy_category_id in energy_category_set:
result['child_space_input']['energy_category_names'].append(
energy_category_dict[energy_category_id]['name'])
result['child_space_input']['units'].append(
energy_category_dict[energy_category_id]['unit_of_measure'])
result['child_space_input']['child_space_names_array'].append(
child_space_input[energy_category_id]['child_space_names'])
result['child_space_input']['subtotals_array'].append(
child_space_input[energy_category_id]['subtotals'])
result['child_space_input']['subtotals_in_kgce_array'].append(
child_space_input[energy_category_id]['subtotals_in_kgce'])
result['child_space_input']['subtotals_in_kgco2e_array'].append(
child_space_input[energy_category_id]['subtotals_in_kgco2e'])
result['child_space_cost'] = dict()
result['child_space_cost']['energy_category_names'] = list() # 1D array [energy category]
result['child_space_cost']['units'] = list() # 1D array [energy category]
result['child_space_cost']['child_space_names_array'] = list() # 2D array [energy category][child space]
result['child_space_cost']['subtotals_array'] = list() # 2D array [energy category][child space]
if energy_category_set is not None and len(energy_category_set) > 0:
for energy_category_id in energy_category_set:
result['child_space_cost']['energy_category_names'].append(
energy_category_dict[energy_category_id]['name'])
result['child_space_cost']['units'].append(config.currency_unit)
result['child_space_cost']['child_space_names_array'].append(
child_space_cost[energy_category_id]['child_space_names'])
result['child_space_cost']['subtotals_array'].append(
child_space_cost[energy_category_id]['subtotals'])
resp.text = json.dumps(result)