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import re |
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from datetime import datetime, timedelta, timezone |
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from decimal import Decimal |
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import falcon |
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import mysql.connector |
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import simplejson as json |
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import config |
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import excelexporters.combinedequipmentstatistics |
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from core import utilities |
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from core.useractivity import access_control, api_key_control |
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class Reporting: |
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def __init__(self): |
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"""Initializes Reporting""" |
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pass |
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@staticmethod |
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def on_options(req, resp): |
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_ = req |
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resp.status = falcon.HTTP_200 |
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#################################################################################################################### |
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# PROCEDURES |
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# Step 1: valid parameters |
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# Step 2: query the combined equipment |
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# Step 3: query energy categories |
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# Step 4: query associated points |
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# Step 5: query associated equipments |
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# Step 6: query base period energy input |
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# Step 7: query reporting period energy input |
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# Step 8: query tariff data |
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# Step 9: query associated points data |
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# Step 10: query associated equipments energy input |
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# Step 11: construct the report |
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#################################################################################################################### |
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@staticmethod |
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def on_get(req, resp): |
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if 'API-KEY' not in req.headers or \ |
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not isinstance(req.headers['API-KEY'], str) or \ |
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len(str.strip(req.headers['API-KEY'])) == 0: |
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access_control(req) |
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else: |
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api_key_control(req) |
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print(req.params) |
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combined_equipment_id = req.params.get('combinedequipmentid') |
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combined_equipment_uuid = req.params.get('combinedequipmentuuid') |
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period_type = req.params.get('periodtype') |
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base_period_start_datetime_local = req.params.get('baseperiodstartdatetime') |
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base_period_end_datetime_local = req.params.get('baseperiodenddatetime') |
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reporting_period_start_datetime_local = req.params.get('reportingperiodstartdatetime') |
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reporting_period_end_datetime_local = req.params.get('reportingperiodenddatetime') |
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language = req.params.get('language') |
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quick_mode = req.params.get('quickmode') |
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################################################################################################################ |
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# Step 1: valid parameters |
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################################################################################################################ |
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if combined_equipment_id is None and combined_equipment_uuid is None: |
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raise falcon.HTTPError(status=falcon.HTTP_400, |
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title='API.BAD_REQUEST', |
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description='API.INVALID_COMBINED_EQUIPMENT_ID') |
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if combined_equipment_id is not None: |
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combined_equipment_id = str.strip(combined_equipment_id) |
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if not combined_equipment_id.isdigit() or int(combined_equipment_id) <= 0: |
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raise falcon.HTTPError(status=falcon.HTTP_400, |
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title='API.BAD_REQUEST', |
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description='API.INVALID_COMBINED_EQUIPMENT_ID') |
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if combined_equipment_uuid is not None: |
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regex = re.compile(r'^[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) |
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match = regex.match(str.strip(combined_equipment_uuid)) |
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if not bool(match): |
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raise falcon.HTTPError(status=falcon.HTTP_400, |
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title='API.BAD_REQUEST', |
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description='API.INVALID_COMBINED_EQUIPMENT_UUID') |
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if period_type is None: |
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raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
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description='API.INVALID_PERIOD_TYPE') |
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else: |
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period_type = str.strip(period_type) |
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if period_type not in ['hourly', 'daily', 'weekly', 'monthly', 'yearly']: |
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raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
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description='API.INVALID_PERIOD_TYPE') |
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timezone_offset = int(config.utc_offset[1:3]) * 60 + int(config.utc_offset[4:6]) |
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if config.utc_offset[0] == '-': |
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timezone_offset = -timezone_offset |
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base_start_datetime_utc = None |
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if base_period_start_datetime_local is not None and len(str.strip(base_period_start_datetime_local)) > 0: |
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base_period_start_datetime_local = str.strip(base_period_start_datetime_local) |
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try: |
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base_start_datetime_utc = datetime.strptime(base_period_start_datetime_local, '%Y-%m-%dT%H:%M:%S') |
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except ValueError: |
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raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
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description="API.INVALID_BASE_PERIOD_START_DATETIME") |
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base_start_datetime_utc = \ |
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base_start_datetime_utc.replace(tzinfo=timezone.utc) - timedelta(minutes=timezone_offset) |
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# nomalize the start datetime |
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if config.minutes_to_count == 30 and base_start_datetime_utc.minute >= 30: |
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base_start_datetime_utc = base_start_datetime_utc.replace(minute=30, second=0, microsecond=0) |
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else: |
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base_start_datetime_utc = base_start_datetime_utc.replace(minute=0, second=0, microsecond=0) |
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base_end_datetime_utc = None |
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if base_period_end_datetime_local is not None and len(str.strip(base_period_end_datetime_local)) > 0: |
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base_period_end_datetime_local = str.strip(base_period_end_datetime_local) |
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try: |
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base_end_datetime_utc = datetime.strptime(base_period_end_datetime_local, '%Y-%m-%dT%H:%M:%S') |
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except ValueError: |
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raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
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description="API.INVALID_BASE_PERIOD_END_DATETIME") |
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base_end_datetime_utc = \ |
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base_end_datetime_utc.replace(tzinfo=timezone.utc) - timedelta(minutes=timezone_offset) |
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if base_start_datetime_utc is not None and base_end_datetime_utc is not None and \ |
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base_start_datetime_utc >= base_end_datetime_utc: |
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raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
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description='API.INVALID_BASE_PERIOD_END_DATETIME') |
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if reporting_period_start_datetime_local is None: |
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raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
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description="API.INVALID_REPORTING_PERIOD_START_DATETIME") |
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else: |
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reporting_period_start_datetime_local = str.strip(reporting_period_start_datetime_local) |
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try: |
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reporting_start_datetime_utc = datetime.strptime(reporting_period_start_datetime_local, |
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'%Y-%m-%dT%H:%M:%S') |
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except ValueError: |
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raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
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description="API.INVALID_REPORTING_PERIOD_START_DATETIME") |
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reporting_start_datetime_utc = \ |
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reporting_start_datetime_utc.replace(tzinfo=timezone.utc) - timedelta(minutes=timezone_offset) |
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# nomalize the start datetime |
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if config.minutes_to_count == 30 and reporting_start_datetime_utc.minute >= 30: |
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reporting_start_datetime_utc = reporting_start_datetime_utc.replace(minute=30, second=0, microsecond=0) |
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else: |
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reporting_start_datetime_utc = reporting_start_datetime_utc.replace(minute=0, second=0, microsecond=0) |
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if reporting_period_end_datetime_local is None: |
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raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
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description="API.INVALID_REPORTING_PERIOD_END_DATETIME") |
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else: |
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reporting_period_end_datetime_local = str.strip(reporting_period_end_datetime_local) |
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try: |
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reporting_end_datetime_utc = datetime.strptime(reporting_period_end_datetime_local, |
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'%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ |
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timedelta(minutes=timezone_offset) |
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except ValueError: |
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raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
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description="API.INVALID_REPORTING_PERIOD_END_DATETIME") |
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if reporting_start_datetime_utc >= reporting_end_datetime_utc: |
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raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
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description='API.INVALID_REPORTING_PERIOD_END_DATETIME') |
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# if turn quick mode on, do not return parameters data and excel file |
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is_quick_mode = False |
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if quick_mode is not None and \ |
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len(str.strip(quick_mode)) > 0 and \ |
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str.lower(str.strip(quick_mode)) in ('true', 't', 'on', 'yes', 'y'): |
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is_quick_mode = True |
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trans = utilities.get_translation(language) |
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trans.install() |
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_ = trans.gettext |
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################################################################################################################ |
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# Step 2: query the combined equipment |
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################################################################################################################ |
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cnx_system = mysql.connector.connect(**config.myems_system_db) |
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cursor_system = cnx_system.cursor() |
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cnx_energy = mysql.connector.connect(**config.myems_energy_db) |
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cursor_energy = cnx_energy.cursor() |
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cnx_historical = mysql.connector.connect(**config.myems_historical_db) |
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cursor_historical = cnx_historical.cursor() |
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if combined_equipment_id is not None: |
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cursor_system.execute(" SELECT id, name, cost_center_id " |
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" FROM tbl_combined_equipments " |
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" WHERE id = %s ", (combined_equipment_id,)) |
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row_combined_equipment = cursor_system.fetchone() |
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elif combined_equipment_uuid is not None: |
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cursor_system.execute(" SELECT id, name, cost_center_id " |
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" FROM tbl_combined_equipments " |
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" WHERE uuid = %s ", (combined_equipment_uuid,)) |
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row_combined_equipment = cursor_system.fetchone() |
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View Code Duplication |
if row_combined_equipment is None: |
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if cursor_system: |
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cursor_system.close() |
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if cnx_system: |
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cnx_system.close() |
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if cursor_energy: |
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cursor_energy.close() |
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if cnx_energy: |
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cnx_energy.close() |
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if cursor_historical: |
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cursor_historical.close() |
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if cnx_historical: |
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cnx_historical.close() |
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raise falcon.HTTPError(status=falcon.HTTP_404, |
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title='API.NOT_FOUND', |
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description='API.COMBINED_EQUIPMENT_NOT_FOUND') |
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combined_equipment = dict() |
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combined_equipment['id'] = row_combined_equipment[0] |
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combined_equipment['name'] = row_combined_equipment[1] |
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combined_equipment['cost_center_id'] = row_combined_equipment[2] |
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################################################################################################################ |
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# Step 3: query energy categories |
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################################################################################################################ |
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energy_category_set = set() |
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# query energy categories in base period |
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cursor_energy.execute(" SELECT DISTINCT(energy_category_id) " |
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" FROM tbl_combined_equipment_input_category_hourly " |
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" WHERE combined_equipment_id = %s " |
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" AND start_datetime_utc >= %s " |
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" AND start_datetime_utc < %s ", |
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(combined_equipment['id'], base_start_datetime_utc, base_end_datetime_utc)) |
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rows_energy_categories = cursor_energy.fetchall() |
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if rows_energy_categories is not None and len(rows_energy_categories) > 0: |
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for row_energy_category in rows_energy_categories: |
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energy_category_set.add(row_energy_category[0]) |
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# query energy categories in reporting period |
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cursor_energy.execute(" SELECT DISTINCT(energy_category_id) " |
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" FROM tbl_combined_equipment_input_category_hourly " |
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" WHERE combined_equipment_id = %s " |
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" AND start_datetime_utc >= %s " |
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" AND start_datetime_utc < %s ", |
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(combined_equipment['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) |
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rows_energy_categories = cursor_energy.fetchall() |
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if rows_energy_categories is not None and len(rows_energy_categories) > 0: |
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for row_energy_category in rows_energy_categories: |
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energy_category_set.add(row_energy_category[0]) |
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# query all energy categories in base period and reporting period |
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cursor_system.execute(" SELECT id, name, unit_of_measure, kgce, kgco2e " |
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" FROM tbl_energy_categories " |
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" ORDER BY id ", ) |
250
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rows_energy_categories = cursor_system.fetchall() |
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if rows_energy_categories is None or len(rows_energy_categories) == 0: |
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if cursor_system: |
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cursor_system.close() |
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if cnx_system: |
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cnx_system.close() |
256
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if cursor_energy: |
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cursor_energy.close() |
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if cnx_energy: |
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cnx_energy.close() |
261
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262
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if cursor_historical: |
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cursor_historical.close() |
264
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if cnx_historical: |
265
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cnx_historical.close() |
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raise falcon.HTTPError(status=falcon.HTTP_404, |
267
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title='API.NOT_FOUND', |
268
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description='API.ENERGY_CATEGORY_NOT_FOUND') |
269
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energy_category_dict = dict() |
270
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for row_energy_category in rows_energy_categories: |
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if row_energy_category[0] in energy_category_set: |
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energy_category_dict[row_energy_category[0]] = {"name": row_energy_category[1], |
273
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"unit_of_measure": row_energy_category[2], |
274
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"kgce": row_energy_category[3], |
275
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"kgco2e": row_energy_category[4]} |
276
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277
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################################################################################################################ |
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# Step 4: query associated points |
279
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################################################################################################################ |
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point_list = list() |
281
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cursor_system.execute(" SELECT p.id, ep.name, p.units, p.object_type " |
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" FROM tbl_combined_equipments e, tbl_combined_equipments_parameters ep, tbl_points p " |
283
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" WHERE e.id = %s AND e.id = ep.combined_equipment_id AND ep.parameter_type = 'point' " |
284
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" AND ep.point_id = p.id " |
285
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" ORDER BY p.id ", (combined_equipment['id'],)) |
286
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rows_points = cursor_system.fetchall() |
287
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if rows_points is not None and len(rows_points) > 0: |
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for row in rows_points: |
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point_list.append({"id": row[0], "name": row[1], "units": row[2], "object_type": row[3]}) |
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################################################################################################################ |
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# Step 5: query associated equipments |
293
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################################################################################################################ |
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associated_equipment_list = list() |
295
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cursor_system.execute(" SELECT e.id, e.name " |
296
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" FROM tbl_equipments e,tbl_combined_equipments_equipments ee" |
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" WHERE ee.combined_equipment_id = %s AND e.id = ee.equipment_id" |
298
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" ORDER BY id ", (combined_equipment['id'],)) |
299
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rows_associated_equipments = cursor_system.fetchall() |
300
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|
|
if rows_associated_equipments is not None and len(rows_associated_equipments) > 0: |
301
|
|
|
for row in rows_associated_equipments: |
302
|
|
|
associated_equipment_list.append({"id": row[0], "name": row[1]}) |
303
|
|
|
|
304
|
|
|
################################################################################################################ |
305
|
|
|
# Step 6: query base period energy input |
306
|
|
|
################################################################################################################ |
307
|
|
|
base = dict() |
308
|
|
|
if energy_category_set is not None and len(energy_category_set) > 0: |
309
|
|
|
for energy_category_id in energy_category_set: |
310
|
|
|
base[energy_category_id] = dict() |
311
|
|
|
base[energy_category_id]['timestamps'] = list() |
312
|
|
|
base[energy_category_id]['values'] = list() |
313
|
|
|
base[energy_category_id]['subtotal'] = Decimal(0.0) |
314
|
|
|
base[energy_category_id]['mean'] = None |
315
|
|
|
base[energy_category_id]['median'] = None |
316
|
|
|
base[energy_category_id]['minimum'] = None |
317
|
|
|
base[energy_category_id]['maximum'] = None |
318
|
|
|
base[energy_category_id]['stdev'] = None |
319
|
|
|
base[energy_category_id]['variance'] = None |
320
|
|
|
|
321
|
|
|
cursor_energy.execute(" SELECT start_datetime_utc, actual_value " |
322
|
|
|
" FROM tbl_combined_equipment_input_category_hourly " |
323
|
|
|
" WHERE combined_equipment_id = %s " |
324
|
|
|
" AND energy_category_id = %s " |
325
|
|
|
" AND start_datetime_utc >= %s " |
326
|
|
|
" AND start_datetime_utc < %s " |
327
|
|
|
" ORDER BY start_datetime_utc ", |
328
|
|
|
(combined_equipment['id'], |
329
|
|
|
energy_category_id, |
330
|
|
|
base_start_datetime_utc, |
331
|
|
|
base_end_datetime_utc)) |
332
|
|
|
rows_combined_equipment_hourly = cursor_energy.fetchall() |
333
|
|
|
|
334
|
|
|
rows_combined_equipment_periodically, \ |
335
|
|
|
base[energy_category_id]['mean'], \ |
336
|
|
|
base[energy_category_id]['median'], \ |
337
|
|
|
base[energy_category_id]['minimum'], \ |
338
|
|
|
base[energy_category_id]['maximum'], \ |
339
|
|
|
base[energy_category_id]['stdev'], \ |
340
|
|
|
base[energy_category_id]['variance'] = \ |
341
|
|
|
utilities.statistics_hourly_data_by_period(rows_combined_equipment_hourly, |
342
|
|
|
base_start_datetime_utc, |
343
|
|
|
base_end_datetime_utc, |
344
|
|
|
period_type) |
345
|
|
|
|
346
|
|
|
for row_combined_equipment_periodically in rows_combined_equipment_periodically: |
347
|
|
|
current_datetime_local = row_combined_equipment_periodically[0].replace(tzinfo=timezone.utc) + \ |
348
|
|
|
timedelta(minutes=timezone_offset) |
349
|
|
|
if period_type == 'hourly': |
350
|
|
|
current_datetime = current_datetime_local.isoformat()[0:19] |
351
|
|
|
elif period_type == 'daily': |
352
|
|
|
current_datetime = current_datetime_local.isoformat()[0:10] |
353
|
|
|
elif period_type == 'weekly': |
354
|
|
|
current_datetime = current_datetime_local.isoformat()[0:10] |
355
|
|
|
elif period_type == 'monthly': |
356
|
|
|
current_datetime = current_datetime_local.isoformat()[0:7] |
357
|
|
|
elif period_type == 'yearly': |
358
|
|
|
current_datetime = current_datetime_local.isoformat()[0:4] |
359
|
|
|
|
360
|
|
|
actual_value = Decimal(0.0) if row_combined_equipment_periodically[1] is None \ |
361
|
|
|
else row_combined_equipment_periodically[1] |
362
|
|
|
base[energy_category_id]['timestamps'].append(current_datetime) |
|
|
|
|
363
|
|
|
base[energy_category_id]['values'].append(actual_value) |
364
|
|
|
base[energy_category_id]['subtotal'] += actual_value |
365
|
|
|
|
366
|
|
|
################################################################################################################ |
367
|
|
|
# Step 7: query reporting period energy input |
368
|
|
|
################################################################################################################ |
369
|
|
|
reporting = dict() |
370
|
|
|
if energy_category_set is not None and len(energy_category_set) > 0: |
371
|
|
|
for energy_category_id in energy_category_set: |
372
|
|
|
reporting[energy_category_id] = dict() |
373
|
|
|
reporting[energy_category_id]['timestamps'] = list() |
374
|
|
|
reporting[energy_category_id]['values'] = list() |
375
|
|
|
reporting[energy_category_id]['subtotal'] = Decimal(0.0) |
376
|
|
|
reporting[energy_category_id]['mean'] = None |
377
|
|
|
reporting[energy_category_id]['median'] = None |
378
|
|
|
reporting[energy_category_id]['minimum'] = None |
379
|
|
|
reporting[energy_category_id]['maximum'] = None |
380
|
|
|
reporting[energy_category_id]['stdev'] = None |
381
|
|
|
reporting[energy_category_id]['variance'] = None |
382
|
|
|
|
383
|
|
|
cursor_energy.execute(" SELECT start_datetime_utc, actual_value " |
384
|
|
|
" FROM tbl_combined_equipment_input_category_hourly " |
385
|
|
|
" WHERE combined_equipment_id = %s " |
386
|
|
|
" AND energy_category_id = %s " |
387
|
|
|
" AND start_datetime_utc >= %s " |
388
|
|
|
" AND start_datetime_utc < %s " |
389
|
|
|
" ORDER BY start_datetime_utc ", |
390
|
|
|
(combined_equipment['id'], |
391
|
|
|
energy_category_id, |
392
|
|
|
reporting_start_datetime_utc, |
393
|
|
|
reporting_end_datetime_utc)) |
394
|
|
|
rows_combined_equipment_hourly = cursor_energy.fetchall() |
395
|
|
|
|
396
|
|
|
rows_combined_equipment_periodically, \ |
397
|
|
|
reporting[energy_category_id]['mean'], \ |
398
|
|
|
reporting[energy_category_id]['median'], \ |
399
|
|
|
reporting[energy_category_id]['minimum'], \ |
400
|
|
|
reporting[energy_category_id]['maximum'], \ |
401
|
|
|
reporting[energy_category_id]['stdev'], \ |
402
|
|
|
reporting[energy_category_id]['variance'] = \ |
403
|
|
|
utilities.statistics_hourly_data_by_period(rows_combined_equipment_hourly, |
404
|
|
|
reporting_start_datetime_utc, |
405
|
|
|
reporting_end_datetime_utc, |
406
|
|
|
period_type) |
407
|
|
|
|
408
|
|
|
for row_combined_equipment_periodically in rows_combined_equipment_periodically: |
409
|
|
|
current_datetime_local = row_combined_equipment_periodically[0].replace(tzinfo=timezone.utc) + \ |
410
|
|
|
timedelta(minutes=timezone_offset) |
411
|
|
|
if period_type == 'hourly': |
412
|
|
|
current_datetime = current_datetime_local.isoformat()[0:19] |
413
|
|
|
elif period_type == 'daily': |
414
|
|
|
current_datetime = current_datetime_local.isoformat()[0:10] |
415
|
|
|
elif period_type == 'weekly': |
416
|
|
|
current_datetime = current_datetime_local.isoformat()[0:10] |
417
|
|
|
elif period_type == 'monthly': |
418
|
|
|
current_datetime = current_datetime_local.isoformat()[0:7] |
419
|
|
|
elif period_type == 'yearly': |
420
|
|
|
current_datetime = current_datetime_local.isoformat()[0:4] |
421
|
|
|
|
422
|
|
|
actual_value = Decimal(0.0) if row_combined_equipment_periodically[1] is None \ |
423
|
|
|
else row_combined_equipment_periodically[1] |
424
|
|
|
reporting[energy_category_id]['timestamps'].append(current_datetime) |
425
|
|
|
reporting[energy_category_id]['values'].append(actual_value) |
426
|
|
|
reporting[energy_category_id]['subtotal'] += actual_value |
427
|
|
|
|
428
|
|
|
################################################################################################################ |
429
|
|
|
# Step 8: query tariff data |
430
|
|
|
################################################################################################################ |
431
|
|
|
parameters_data = dict() |
432
|
|
|
parameters_data['names'] = list() |
433
|
|
|
parameters_data['timestamps'] = list() |
434
|
|
|
parameters_data['values'] = list() |
435
|
|
|
if not is_quick_mode: |
436
|
|
|
if config.is_tariff_appended and energy_category_set is not None and len(energy_category_set) > 0: |
437
|
|
|
for energy_category_id in energy_category_set: |
438
|
|
|
energy_category_tariff_dict = \ |
439
|
|
|
utilities.get_energy_category_tariffs(combined_equipment['cost_center_id'], |
440
|
|
|
energy_category_id, |
441
|
|
|
reporting_start_datetime_utc, |
442
|
|
|
reporting_end_datetime_utc) |
443
|
|
|
tariff_timestamp_list = list() |
444
|
|
|
tariff_value_list = list() |
445
|
|
|
for k, v in energy_category_tariff_dict.items(): |
446
|
|
|
# convert k from utc to local |
447
|
|
|
k = k + timedelta(minutes=timezone_offset) |
448
|
|
|
tariff_timestamp_list.append(k.isoformat()[0:19]) |
449
|
|
|
tariff_value_list.append(v) |
450
|
|
|
|
451
|
|
|
parameters_data['names'].append( |
452
|
|
|
_('Tariff') + '-' + energy_category_dict[energy_category_id]['name']) |
453
|
|
|
parameters_data['timestamps'].append(tariff_timestamp_list) |
454
|
|
|
parameters_data['values'].append(tariff_value_list) |
455
|
|
|
|
456
|
|
|
################################################################################################################ |
457
|
|
|
# Step 9: query associated points data |
458
|
|
|
################################################################################################################ |
459
|
|
|
if not is_quick_mode: |
460
|
|
|
for point in point_list: |
461
|
|
|
point_values = [] |
462
|
|
|
point_timestamps = [] |
463
|
|
|
if point['object_type'] == 'ENERGY_VALUE': |
464
|
|
|
query = (" SELECT utc_date_time, actual_value " |
465
|
|
|
" FROM tbl_energy_value " |
466
|
|
|
" WHERE point_id = %s " |
467
|
|
|
" AND utc_date_time BETWEEN %s AND %s " |
468
|
|
|
" ORDER BY utc_date_time ") |
469
|
|
|
cursor_historical.execute(query, (point['id'], |
470
|
|
|
reporting_start_datetime_utc, |
471
|
|
|
reporting_end_datetime_utc)) |
472
|
|
|
rows = cursor_historical.fetchall() |
473
|
|
|
|
474
|
|
|
if rows is not None and len(rows) > 0: |
475
|
|
|
for row in rows: |
476
|
|
|
current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ |
477
|
|
|
timedelta(minutes=timezone_offset) |
478
|
|
|
current_datetime = current_datetime_local.isoformat()[0:19] |
479
|
|
|
point_timestamps.append(current_datetime) |
480
|
|
|
point_values.append(row[1]) |
481
|
|
|
elif point['object_type'] == 'ANALOG_VALUE': |
482
|
|
|
query = (" SELECT utc_date_time, actual_value " |
483
|
|
|
" FROM tbl_analog_value " |
484
|
|
|
" WHERE point_id = %s " |
485
|
|
|
" AND utc_date_time BETWEEN %s AND %s " |
486
|
|
|
" ORDER BY utc_date_time ") |
487
|
|
|
cursor_historical.execute(query, (point['id'], |
488
|
|
|
reporting_start_datetime_utc, |
489
|
|
|
reporting_end_datetime_utc)) |
490
|
|
|
rows = cursor_historical.fetchall() |
491
|
|
|
|
492
|
|
|
if rows is not None and len(rows) > 0: |
493
|
|
|
for row in rows: |
494
|
|
|
current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ |
495
|
|
|
timedelta(minutes=timezone_offset) |
496
|
|
|
current_datetime = current_datetime_local.isoformat()[0:19] |
497
|
|
|
point_timestamps.append(current_datetime) |
498
|
|
|
point_values.append(row[1]) |
499
|
|
|
elif point['object_type'] == 'DIGITAL_VALUE': |
500
|
|
|
query = (" SELECT utc_date_time, actual_value " |
501
|
|
|
" FROM tbl_digital_value " |
502
|
|
|
" WHERE point_id = %s " |
503
|
|
|
" AND utc_date_time BETWEEN %s AND %s " |
504
|
|
|
" ORDER BY utc_date_time ") |
505
|
|
|
cursor_historical.execute(query, (point['id'], |
506
|
|
|
reporting_start_datetime_utc, |
507
|
|
|
reporting_end_datetime_utc)) |
508
|
|
|
rows = cursor_historical.fetchall() |
509
|
|
|
|
510
|
|
|
if rows is not None and len(rows) > 0: |
511
|
|
|
for row in rows: |
512
|
|
|
current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ |
513
|
|
|
timedelta(minutes=timezone_offset) |
514
|
|
|
current_datetime = current_datetime_local.isoformat()[0:19] |
515
|
|
|
point_timestamps.append(current_datetime) |
516
|
|
|
point_values.append(row[1]) |
517
|
|
|
|
518
|
|
|
parameters_data['names'].append(point['name'] + ' (' + point['units'] + ')') |
519
|
|
|
parameters_data['timestamps'].append(point_timestamps) |
520
|
|
|
parameters_data['values'].append(point_values) |
521
|
|
|
|
522
|
|
|
################################################################################################################ |
523
|
|
|
# Step 10: query associated equipments energy input |
524
|
|
|
################################################################################################################ |
525
|
|
|
associated_equipment_data = dict() |
526
|
|
|
|
527
|
|
|
if energy_category_set is not None and len(energy_category_set) > 0: |
528
|
|
|
for energy_category_id in energy_category_set: |
529
|
|
|
associated_equipment_data[energy_category_id] = dict() |
530
|
|
|
associated_equipment_data[energy_category_id]['associated_equipment_names'] = list() |
531
|
|
|
associated_equipment_data[energy_category_id]['subtotals'] = list() |
532
|
|
|
for associated_equipment in associated_equipment_list: |
533
|
|
|
associated_equipment_data[energy_category_id]['associated_equipment_names'].append( |
534
|
|
|
associated_equipment['name']) |
535
|
|
|
|
536
|
|
|
cursor_energy.execute(" SELECT SUM(actual_value) " |
537
|
|
|
" FROM tbl_equipment_input_category_hourly " |
538
|
|
|
" WHERE equipment_id = %s " |
539
|
|
|
" AND energy_category_id = %s " |
540
|
|
|
" AND start_datetime_utc >= %s " |
541
|
|
|
" AND start_datetime_utc < %s ", |
542
|
|
|
(associated_equipment['id'], |
543
|
|
|
energy_category_id, |
544
|
|
|
reporting_start_datetime_utc, |
545
|
|
|
reporting_end_datetime_utc)) |
546
|
|
|
row_subtotal = cursor_energy.fetchone() |
547
|
|
|
|
548
|
|
|
subtotal = Decimal(0.0) if (row_subtotal is None or row_subtotal[0] is None) else row_subtotal[0] |
549
|
|
|
associated_equipment_data[energy_category_id]['subtotals'].append(subtotal) |
550
|
|
|
|
551
|
|
|
################################################################################################################ |
552
|
|
|
# Step 11: construct the report |
553
|
|
|
################################################################################################################ |
554
|
|
|
if cursor_system: |
555
|
|
|
cursor_system.close() |
556
|
|
|
if cnx_system: |
557
|
|
|
cnx_system.close() |
558
|
|
|
|
559
|
|
|
if cursor_energy: |
560
|
|
|
cursor_energy.close() |
561
|
|
|
if cnx_energy: |
562
|
|
|
cnx_energy.close() |
563
|
|
|
|
564
|
|
|
if cursor_historical: |
565
|
|
|
cursor_historical.close() |
566
|
|
|
if cnx_historical: |
567
|
|
|
cnx_historical.close() |
568
|
|
|
|
569
|
|
|
result = dict() |
570
|
|
|
|
571
|
|
|
result['combined_equipment'] = dict() |
572
|
|
|
result['combined_equipment']['name'] = combined_equipment['name'] |
573
|
|
|
|
574
|
|
|
result['base_period'] = dict() |
575
|
|
|
result['base_period']['names'] = list() |
576
|
|
|
result['base_period']['units'] = list() |
577
|
|
|
result['base_period']['timestamps'] = list() |
578
|
|
|
result['base_period']['values'] = list() |
579
|
|
|
result['base_period']['subtotals'] = list() |
580
|
|
|
result['base_period']['means'] = list() |
581
|
|
|
result['base_period']['medians'] = list() |
582
|
|
|
result['base_period']['minimums'] = list() |
583
|
|
|
result['base_period']['maximums'] = list() |
584
|
|
|
result['base_period']['stdevs'] = list() |
585
|
|
|
result['base_period']['variances'] = list() |
586
|
|
|
|
587
|
|
|
if energy_category_set is not None and len(energy_category_set) > 0: |
588
|
|
|
for energy_category_id in energy_category_set: |
589
|
|
|
result['base_period']['names'].append(energy_category_dict[energy_category_id]['name']) |
590
|
|
|
result['base_period']['units'].append(energy_category_dict[energy_category_id]['unit_of_measure']) |
591
|
|
|
result['base_period']['timestamps'].append(base[energy_category_id]['timestamps']) |
592
|
|
|
result['base_period']['values'].append(base[energy_category_id]['values']) |
593
|
|
|
result['base_period']['subtotals'].append(base[energy_category_id]['subtotal']) |
594
|
|
|
result['base_period']['means'].append(base[energy_category_id]['mean']) |
595
|
|
|
result['base_period']['medians'].append(base[energy_category_id]['median']) |
596
|
|
|
result['base_period']['minimums'].append(base[energy_category_id]['minimum']) |
597
|
|
|
result['base_period']['maximums'].append(base[energy_category_id]['maximum']) |
598
|
|
|
result['base_period']['stdevs'].append(base[energy_category_id]['stdev']) |
599
|
|
|
result['base_period']['variances'].append(base[energy_category_id]['variance']) |
600
|
|
|
|
601
|
|
|
result['reporting_period'] = dict() |
602
|
|
|
result['reporting_period']['names'] = list() |
603
|
|
|
result['reporting_period']['energy_category_ids'] = list() |
604
|
|
|
result['reporting_period']['units'] = list() |
605
|
|
|
result['reporting_period']['timestamps'] = list() |
606
|
|
|
result['reporting_period']['values'] = list() |
607
|
|
|
result['reporting_period']['rates'] = list() |
608
|
|
|
result['reporting_period']['subtotals'] = list() |
609
|
|
|
result['reporting_period']['means'] = list() |
610
|
|
|
result['reporting_period']['means_increment_rate'] = list() |
611
|
|
|
result['reporting_period']['medians'] = list() |
612
|
|
|
result['reporting_period']['medians_increment_rate'] = list() |
613
|
|
|
result['reporting_period']['minimums'] = list() |
614
|
|
|
result['reporting_period']['minimums_increment_rate'] = list() |
615
|
|
|
result['reporting_period']['maximums'] = list() |
616
|
|
|
result['reporting_period']['maximums_increment_rate'] = list() |
617
|
|
|
result['reporting_period']['stdevs'] = list() |
618
|
|
|
result['reporting_period']['stdevs_increment_rate'] = list() |
619
|
|
|
result['reporting_period']['variances'] = list() |
620
|
|
|
result['reporting_period']['variances_increment_rate'] = list() |
621
|
|
|
|
622
|
|
View Code Duplication |
if energy_category_set is not None and len(energy_category_set) > 0: |
|
|
|
|
623
|
|
|
for energy_category_id in energy_category_set: |
624
|
|
|
result['reporting_period']['names'].append(energy_category_dict[energy_category_id]['name']) |
625
|
|
|
result['reporting_period']['energy_category_ids'].append(energy_category_id) |
626
|
|
|
result['reporting_period']['units'].append(energy_category_dict[energy_category_id]['unit_of_measure']) |
627
|
|
|
result['reporting_period']['timestamps'].append(reporting[energy_category_id]['timestamps']) |
628
|
|
|
result['reporting_period']['values'].append(reporting[energy_category_id]['values']) |
629
|
|
|
result['reporting_period']['subtotals'].append(reporting[energy_category_id]['subtotal']) |
630
|
|
|
result['reporting_period']['means'].append(reporting[energy_category_id]['mean']) |
631
|
|
|
result['reporting_period']['means_increment_rate'].append( |
632
|
|
|
(reporting[energy_category_id]['mean'] - base[energy_category_id]['mean']) / |
633
|
|
|
base[energy_category_id]['mean'] if (base[energy_category_id]['mean'] is not None and |
634
|
|
|
base[energy_category_id]['mean'] > Decimal(0.0)) |
635
|
|
|
else None) |
636
|
|
|
result['reporting_period']['medians'].append(reporting[energy_category_id]['median']) |
637
|
|
|
result['reporting_period']['medians_increment_rate'].append( |
638
|
|
|
(reporting[energy_category_id]['median'] - base[energy_category_id]['median']) / |
639
|
|
|
base[energy_category_id]['median'] if (base[energy_category_id]['median'] is not None and |
640
|
|
|
base[energy_category_id]['median'] > Decimal(0.0)) |
641
|
|
|
else None) |
642
|
|
|
result['reporting_period']['minimums'].append(reporting[energy_category_id]['minimum']) |
643
|
|
|
result['reporting_period']['minimums_increment_rate'].append( |
644
|
|
|
(reporting[energy_category_id]['minimum'] - base[energy_category_id]['minimum']) / |
645
|
|
|
base[energy_category_id]['minimum'] if (base[energy_category_id]['minimum'] is not None and |
646
|
|
|
base[energy_category_id]['minimum'] > Decimal(0.0)) |
647
|
|
|
else None) |
648
|
|
|
result['reporting_period']['maximums'].append(reporting[energy_category_id]['maximum']) |
649
|
|
|
result['reporting_period']['maximums_increment_rate'].append( |
650
|
|
|
(reporting[energy_category_id]['maximum'] - base[energy_category_id]['maximum']) / |
651
|
|
|
base[energy_category_id]['maximum'] if (base[energy_category_id]['maximum'] is not None and |
652
|
|
|
base[energy_category_id]['maximum'] > Decimal(0.0)) |
653
|
|
|
else None) |
654
|
|
|
result['reporting_period']['stdevs'].append(reporting[energy_category_id]['stdev']) |
655
|
|
|
result['reporting_period']['stdevs_increment_rate'].append( |
656
|
|
|
(reporting[energy_category_id]['stdev'] - base[energy_category_id]['stdev']) / |
657
|
|
|
base[energy_category_id]['stdev'] if (base[energy_category_id]['stdev'] is not None and |
658
|
|
|
base[energy_category_id]['stdev'] > Decimal(0.0)) |
659
|
|
|
else None) |
660
|
|
|
result['reporting_period']['variances'].append(reporting[energy_category_id]['variance']) |
661
|
|
|
result['reporting_period']['variances_increment_rate'].append( |
662
|
|
|
(reporting[energy_category_id]['variance'] - base[energy_category_id]['variance']) / |
663
|
|
|
base[energy_category_id]['variance'] if (base[energy_category_id]['variance'] is not None and |
664
|
|
|
base[energy_category_id]['variance'] > Decimal(0.0)) |
665
|
|
|
else None) |
666
|
|
|
|
667
|
|
|
rate = list() |
668
|
|
|
for index, value in enumerate(reporting[energy_category_id]['values']): |
669
|
|
|
if index < len(base[energy_category_id]['values']) \ |
670
|
|
|
and base[energy_category_id]['values'][index] != 0 and value != 0: |
671
|
|
|
rate.append((value - base[energy_category_id]['values'][index]) |
672
|
|
|
/ base[energy_category_id]['values'][index]) |
673
|
|
|
else: |
674
|
|
|
rate.append(None) |
675
|
|
|
result['reporting_period']['rates'].append(rate) |
676
|
|
|
|
677
|
|
|
result['parameters'] = { |
678
|
|
|
"names": parameters_data['names'], |
679
|
|
|
"timestamps": parameters_data['timestamps'], |
680
|
|
|
"values": parameters_data['values'] |
681
|
|
|
} |
682
|
|
|
|
683
|
|
|
result['associated_equipment'] = dict() |
684
|
|
|
result['associated_equipment']['energy_category_names'] = list() |
685
|
|
|
result['associated_equipment']['units'] = list() |
686
|
|
|
result['associated_equipment']['associated_equipment_names_array'] = list() |
687
|
|
|
result['associated_equipment']['subtotals_array'] = list() |
688
|
|
|
if energy_category_set is not None and len(energy_category_set) > 0: |
689
|
|
|
for energy_category_id in energy_category_set: |
690
|
|
|
result['associated_equipment']['energy_category_names'].append( |
691
|
|
|
energy_category_dict[energy_category_id]['name']) |
692
|
|
|
result['associated_equipment']['units'].append( |
693
|
|
|
energy_category_dict[energy_category_id]['unit_of_measure']) |
694
|
|
|
result['associated_equipment']['associated_equipment_names_array'].append( |
695
|
|
|
associated_equipment_data[energy_category_id]['associated_equipment_names']) |
696
|
|
|
result['associated_equipment']['subtotals_array'].append( |
697
|
|
|
associated_equipment_data[energy_category_id]['subtotals']) |
698
|
|
|
|
699
|
|
|
# export result to Excel file and then encode the file to base64 string |
700
|
|
|
result['excel_bytes_base64'] = None |
701
|
|
|
if not is_quick_mode: |
702
|
|
|
result['excel_bytes_base64'] = \ |
703
|
|
|
excelexporters.combinedequipmentstatistics.export(result, |
704
|
|
|
combined_equipment['name'], |
705
|
|
|
base_period_start_datetime_local, |
706
|
|
|
base_period_end_datetime_local, |
707
|
|
|
reporting_period_start_datetime_local, |
708
|
|
|
reporting_period_end_datetime_local, |
709
|
|
|
period_type, |
710
|
|
|
language) |
711
|
|
|
|
712
|
|
|
resp.text = json.dumps(result) |
713
|
|
|
|