730 lines
44 KiB
Python
730 lines
44 KiB
Python
import re
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import falcon
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import simplejson as json
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import mysql.connector
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import config
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from datetime import datetime, timedelta, timezone
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from core import utilities
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from decimal import Decimal
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import excelexporters.shopfloorsaving
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class Reporting:
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@staticmethod
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def __init__():
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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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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 shopfloor
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# Step 3: query energy categories
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# Step 4: query associated sensors
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# Step 5: query associated points
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# Step 6: query base period energy saving
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# Step 7: query reporting period energy saving
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# Step 8: query tariff data
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# Step 9: query associated sensors and points data
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# Step 10: 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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print(req.params)
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shopfloor_id = req.params.get('shopfloorid')
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shopfloor_uuid = req.params.get('shopflooruuid')
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period_type = req.params.get('periodtype')
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base_start_datetime_local = req.params.get('baseperiodstartdatetime')
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base_end_datetime_local = req.params.get('baseperiodenddatetime')
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reporting_start_datetime_local = req.params.get('reportingperiodstartdatetime')
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reporting_end_datetime_local = req.params.get('reportingperiodenddatetime')
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################################################################################################################
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# Step 1: valid parameters
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################################################################################################################
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if shopfloor_id is None and shopfloor_uuid is None:
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raise falcon.HTTPError(falcon.HTTP_400,
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title='API.BAD_REQUEST',
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description='API.INVALID_SHOPFLOOR_ID')
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if shopfloor_id is not None:
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shopfloor_id = str.strip(shopfloor_id)
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if not shopfloor_id.isdigit() or int(shopfloor_id) <= 0:
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raise falcon.HTTPError(falcon.HTTP_400,
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title='API.BAD_REQUEST',
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description='API.INVALID_SHOPFLOOR_ID')
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if shopfloor_uuid is not None:
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shopfloor_uuid = str.strip(shopfloor_uuid)
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regex = re.compile('^[a-f0-9]{8}-?[a-f0-9]{4}-?4[a-f0-9]{3}-?[89ab][a-f0-9]{3}-?[a-f0-9]{12}\Z', re.I)
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match = regex.match(shopfloor_uuid)
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if not bool(match):
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raise falcon.HTTPError(falcon.HTTP_400,
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title='API.BAD_REQUEST',
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description='API.INVALID_SHOPFLOOR_UUID')
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if period_type is None:
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raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', 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(falcon.HTTP_400, title='API.BAD_REQUEST', 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_start_datetime_local is not None and len(str.strip(base_start_datetime_local)) > 0:
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base_start_datetime_local = str.strip(base_start_datetime_local)
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try:
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base_start_datetime_utc = datetime.strptime(base_start_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(falcon.HTTP_400, title='API.BAD_REQUEST',
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description="API.INVALID_BASE_PERIOD_START_DATETIME")
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base_end_datetime_utc = None
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if base_end_datetime_local is not None and len(str.strip(base_end_datetime_local)) > 0:
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base_end_datetime_local = str.strip(base_end_datetime_local)
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try:
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base_end_datetime_utc = datetime.strptime(base_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(falcon.HTTP_400, title='API.BAD_REQUEST',
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description="API.INVALID_BASE_PERIOD_END_DATETIME")
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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(falcon.HTTP_400, title='API.BAD_REQUEST',
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description='API.INVALID_BASE_PERIOD_END_DATETIME')
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if reporting_start_datetime_local is None:
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raise falcon.HTTPError(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_start_datetime_local = str.strip(reporting_start_datetime_local)
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try:
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reporting_start_datetime_utc = datetime.strptime(reporting_start_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(falcon.HTTP_400, title='API.BAD_REQUEST',
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description="API.INVALID_REPORTING_PERIOD_START_DATETIME")
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if reporting_end_datetime_local is None:
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raise falcon.HTTPError(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_end_datetime_local = str.strip(reporting_end_datetime_local)
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try:
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reporting_end_datetime_utc = datetime.strptime(reporting_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(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(falcon.HTTP_400, title='API.BAD_REQUEST',
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description='API.INVALID_REPORTING_PERIOD_END_DATETIME')
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################################################################################################################
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# Step 2: query the shopfloor
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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_energy_baseline = mysql.connector.connect(**config.myems_energy_baseline_db)
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cursor_energy_baseline = cnx_energy_baseline.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 shopfloor_id is not None:
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cursor_system.execute(" SELECT id, name, area, cost_center_id "
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" FROM tbl_shopfloors "
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" WHERE id = %s ", (shopfloor_id,))
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row_shopfloor = cursor_system.fetchone()
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elif shopfloor_uuid is not None:
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cursor_system.execute(" SELECT id, name, area, cost_center_id "
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" FROM tbl_shopfloors "
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" WHERE uuid = %s ", (shopfloor_uuid,))
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row_shopfloor = cursor_system.fetchone()
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if row_shopfloor 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.disconnect()
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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.disconnect()
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if cursor_energy_baseline:
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cursor_energy_baseline.close()
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if cnx_energy_baseline:
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cnx_energy_baseline.disconnect()
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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.disconnect()
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raise falcon.HTTPError(falcon.HTTP_404, title='API.NOT_FOUND', description='API.SHOPFLOOR_NOT_FOUND')
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shopfloor = dict()
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shopfloor['id'] = row_shopfloor[0]
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shopfloor['name'] = row_shopfloor[1]
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shopfloor['area'] = row_shopfloor[2]
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shopfloor['cost_center_id'] = row_shopfloor[3]
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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_shopfloor_input_category_hourly "
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" WHERE shopfloor_id = %s "
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" AND start_datetime_utc >= %s "
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" AND start_datetime_utc < %s ",
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(shopfloor['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 or 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_shopfloor_input_category_hourly "
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" WHERE shopfloor_id = %s "
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" AND start_datetime_utc >= %s "
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" AND start_datetime_utc < %s ",
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(shopfloor['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 or 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 ", )
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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.disconnect()
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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.disconnect()
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if cursor_energy_baseline:
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cursor_energy_baseline.close()
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if cnx_energy_baseline:
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cnx_energy_baseline.disconnect()
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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.disconnect()
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raise falcon.HTTPError(falcon.HTTP_404,
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title='API.NOT_FOUND',
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description='API.ENERGY_CATEGORY_NOT_FOUND')
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energy_category_dict = dict()
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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],
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"unit_of_measure": row_energy_category[2],
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"kgce": row_energy_category[3],
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"kgco2e": row_energy_category[4]}
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################################################################################################################
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# Step 4: query associated sensors
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################################################################################################################
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point_list = list()
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cursor_system.execute(" SELECT p.id, p.name, p.units, p.object_type "
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" FROM tbl_shopfloors st, tbl_sensors se, tbl_shopfloors_sensors ss, "
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" tbl_points p, tbl_sensors_points sp "
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" WHERE st.id = %s AND st.id = ss.shopfloor_id AND ss.sensor_id = se.id "
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" AND se.id = sp.sensor_id AND sp.point_id = p.id "
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" ORDER BY p.id ", (shopfloor['id'],))
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rows_points = cursor_system.fetchall()
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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 points
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################################################################################################################
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cursor_system.execute(" SELECT p.id, p.name, p.units, p.object_type "
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" FROM tbl_shopfloors s, tbl_shopfloors_points sp, tbl_points p "
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" WHERE s.id = %s AND s.id = sp.shopfloor_id AND sp.point_id = p.id "
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" ORDER BY p.id ", (shopfloor['id'],))
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rows_points = cursor_system.fetchall()
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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 6: query base period energy saving
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################################################################################################################
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base = dict()
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if energy_category_set is not None and len(energy_category_set) > 0:
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for energy_category_id in energy_category_set:
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kgce = energy_category_dict[energy_category_id]['kgce']
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kgco2e = energy_category_dict[energy_category_id]['kgco2e']
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base[energy_category_id] = dict()
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base[energy_category_id]['timestamps'] = list()
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base[energy_category_id]['values_baseline'] = list()
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base[energy_category_id]['values_actual'] = list()
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base[energy_category_id]['values_saving'] = list()
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base[energy_category_id]['subtotal_baseline'] = Decimal(0.0)
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base[energy_category_id]['subtotal_actual'] = Decimal(0.0)
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base[energy_category_id]['subtotal_saving'] = Decimal(0.0)
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base[energy_category_id]['subtotal_in_kgce_baseline'] = Decimal(0.0)
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base[energy_category_id]['subtotal_in_kgce_actual'] = Decimal(0.0)
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base[energy_category_id]['subtotal_in_kgce_saving'] = Decimal(0.0)
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base[energy_category_id]['subtotal_in_kgco2e_baseline'] = Decimal(0.0)
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base[energy_category_id]['subtotal_in_kgco2e_actual'] = Decimal(0.0)
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base[energy_category_id]['subtotal_in_kgco2e_saving'] = Decimal(0.0)
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# query base period's energy baseline
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cursor_energy_baseline.execute(" SELECT start_datetime_utc, actual_value "
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" FROM tbl_shopfloor_input_category_hourly "
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" WHERE shopfloor_id = %s "
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" AND energy_category_id = %s "
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" AND start_datetime_utc >= %s "
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" AND start_datetime_utc < %s "
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" ORDER BY start_datetime_utc ",
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(shopfloor['id'],
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energy_category_id,
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base_start_datetime_utc,
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base_end_datetime_utc))
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rows_shopfloor_hourly = cursor_energy_baseline.fetchall()
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rows_shopfloor_periodically = utilities.aggregate_hourly_data_by_period(rows_shopfloor_hourly,
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base_start_datetime_utc,
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base_end_datetime_utc,
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period_type)
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for row_shopfloor_periodically in rows_shopfloor_periodically:
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current_datetime_local = row_shopfloor_periodically[0].replace(tzinfo=timezone.utc) + \
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timedelta(minutes=timezone_offset)
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if period_type == 'hourly':
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current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S')
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elif period_type == 'daily':
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current_datetime = current_datetime_local.strftime('%Y-%m-%d')
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elif period_type == 'weekly':
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current_datetime = current_datetime_local.strftime('%Y-%m-%d')
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elif period_type == 'monthly':
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current_datetime = current_datetime_local.strftime('%Y-%m')
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elif period_type == 'yearly':
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current_datetime = current_datetime_local.strftime('%Y')
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baseline_value = Decimal(0.0) if row_shopfloor_periodically[1] is None \
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else row_shopfloor_periodically[1]
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base[energy_category_id]['timestamps'].append(current_datetime)
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base[energy_category_id]['values_baseline'].append(baseline_value)
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base[energy_category_id]['subtotal_baseline'] += baseline_value
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base[energy_category_id]['subtotal_in_kgce_baseline'] += baseline_value * kgce
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base[energy_category_id]['subtotal_in_kgco2e_baseline'] += baseline_value * kgco2e
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# query base period's energy actual
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cursor_energy.execute(" SELECT start_datetime_utc, actual_value "
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" FROM tbl_shopfloor_input_category_hourly "
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" WHERE shopfloor_id = %s "
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" AND energy_category_id = %s "
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" AND start_datetime_utc >= %s "
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" AND start_datetime_utc < %s "
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" ORDER BY start_datetime_utc ",
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(shopfloor['id'],
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energy_category_id,
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base_start_datetime_utc,
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base_end_datetime_utc))
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rows_shopfloor_hourly = cursor_energy.fetchall()
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rows_shopfloor_periodically = utilities.aggregate_hourly_data_by_period(rows_shopfloor_hourly,
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base_start_datetime_utc,
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base_end_datetime_utc,
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period_type)
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for row_shopfloor_periodically in rows_shopfloor_periodically:
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current_datetime_local = row_shopfloor_periodically[0].replace(tzinfo=timezone.utc) + \
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timedelta(minutes=timezone_offset)
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if period_type == 'hourly':
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current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S')
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elif period_type == 'daily':
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current_datetime = current_datetime_local.strftime('%Y-%m-%d')
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elif period_type == 'weekly':
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current_datetime = current_datetime_local.strftime('%Y-%m-%d')
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elif period_type == 'monthly':
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current_datetime = current_datetime_local.strftime('%Y-%m')
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elif period_type == 'yearly':
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current_datetime = current_datetime_local.strftime('%Y')
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actual_value = Decimal(0.0) if row_shopfloor_periodically[1] is None \
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else row_shopfloor_periodically[1]
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base[energy_category_id]['values_actual'].append(actual_value)
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base[energy_category_id]['subtotal_actual'] += actual_value
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base[energy_category_id]['subtotal_in_kgce_actual'] += actual_value * kgce
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base[energy_category_id]['subtotal_in_kgco2e_actual'] += actual_value * kgco2e
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# calculate base period's energy savings
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for i in range(len(base[energy_category_id]['values_baseline'])):
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base[energy_category_id]['values_saving'].append(
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base[energy_category_id]['values_baseline'][i] -
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base[energy_category_id]['values_actual'][i])
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base[energy_category_id]['subtotal_saving'] = \
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base[energy_category_id]['subtotal_baseline'] - \
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base[energy_category_id]['subtotal_actual']
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base[energy_category_id]['subtotal_in_kgce_saving'] = \
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base[energy_category_id]['subtotal_in_kgce_baseline'] - \
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base[energy_category_id]['subtotal_in_kgce_actual']
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base[energy_category_id]['subtotal_in_kgco2e_saving'] = \
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base[energy_category_id]['subtotal_in_kgco2e_baseline'] - \
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base[energy_category_id]['subtotal_in_kgco2e_actual']
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################################################################################################################
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# Step 7: query reporting period energy saving
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################################################################################################################
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reporting = dict()
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if energy_category_set is not None and len(energy_category_set) > 0:
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for energy_category_id in energy_category_set:
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kgce = energy_category_dict[energy_category_id]['kgce']
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kgco2e = energy_category_dict[energy_category_id]['kgco2e']
|
|
|
|
reporting[energy_category_id] = dict()
|
|
reporting[energy_category_id]['timestamps'] = list()
|
|
reporting[energy_category_id]['values_baseline'] = list()
|
|
reporting[energy_category_id]['values_actual'] = list()
|
|
reporting[energy_category_id]['values_saving'] = list()
|
|
reporting[energy_category_id]['subtotal_baseline'] = Decimal(0.0)
|
|
reporting[energy_category_id]['subtotal_actual'] = Decimal(0.0)
|
|
reporting[energy_category_id]['subtotal_saving'] = Decimal(0.0)
|
|
reporting[energy_category_id]['subtotal_in_kgce_baseline'] = Decimal(0.0)
|
|
reporting[energy_category_id]['subtotal_in_kgce_actual'] = Decimal(0.0)
|
|
reporting[energy_category_id]['subtotal_in_kgce_saving'] = Decimal(0.0)
|
|
reporting[energy_category_id]['subtotal_in_kgco2e_baseline'] = Decimal(0.0)
|
|
reporting[energy_category_id]['subtotal_in_kgco2e_actual'] = Decimal(0.0)
|
|
reporting[energy_category_id]['subtotal_in_kgco2e_saving'] = Decimal(0.0)
|
|
# query reporting period's energy baseline
|
|
cursor_energy_baseline.execute(" SELECT start_datetime_utc, actual_value "
|
|
" FROM tbl_shopfloor_input_category_hourly "
|
|
" WHERE shopfloor_id = %s "
|
|
" AND energy_category_id = %s "
|
|
" AND start_datetime_utc >= %s "
|
|
" AND start_datetime_utc < %s "
|
|
" ORDER BY start_datetime_utc ",
|
|
(shopfloor['id'],
|
|
energy_category_id,
|
|
reporting_start_datetime_utc,
|
|
reporting_end_datetime_utc))
|
|
rows_shopfloor_hourly = cursor_energy_baseline.fetchall()
|
|
|
|
rows_shopfloor_periodically = utilities.aggregate_hourly_data_by_period(rows_shopfloor_hourly,
|
|
reporting_start_datetime_utc,
|
|
reporting_end_datetime_utc,
|
|
period_type)
|
|
for row_shopfloor_periodically in rows_shopfloor_periodically:
|
|
current_datetime_local = row_shopfloor_periodically[0].replace(tzinfo=timezone.utc) + \
|
|
timedelta(minutes=timezone_offset)
|
|
if period_type == 'hourly':
|
|
current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S')
|
|
elif period_type == 'daily':
|
|
current_datetime = current_datetime_local.strftime('%Y-%m-%d')
|
|
elif period_type == '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')
|
|
|
|
baseline_value = Decimal(0.0) if row_shopfloor_periodically[1] is None \
|
|
else row_shopfloor_periodically[1]
|
|
reporting[energy_category_id]['timestamps'].append(current_datetime)
|
|
reporting[energy_category_id]['values_baseline'].append(baseline_value)
|
|
reporting[energy_category_id]['subtotal_baseline'] += baseline_value
|
|
reporting[energy_category_id]['subtotal_in_kgce_baseline'] += baseline_value * kgce
|
|
reporting[energy_category_id]['subtotal_in_kgco2e_baseline'] += baseline_value * kgco2e
|
|
|
|
# query reporting period's energy actual
|
|
cursor_energy.execute(" SELECT start_datetime_utc, actual_value "
|
|
" FROM tbl_shopfloor_input_category_hourly "
|
|
" WHERE shopfloor_id = %s "
|
|
" AND energy_category_id = %s "
|
|
" AND start_datetime_utc >= %s "
|
|
" AND start_datetime_utc < %s "
|
|
" ORDER BY start_datetime_utc ",
|
|
(shopfloor['id'],
|
|
energy_category_id,
|
|
reporting_start_datetime_utc,
|
|
reporting_end_datetime_utc))
|
|
rows_shopfloor_hourly = cursor_energy.fetchall()
|
|
|
|
rows_shopfloor_periodically = utilities.aggregate_hourly_data_by_period(rows_shopfloor_hourly,
|
|
reporting_start_datetime_utc,
|
|
reporting_end_datetime_utc,
|
|
period_type)
|
|
for row_shopfloor_periodically in rows_shopfloor_periodically:
|
|
current_datetime_local = row_shopfloor_periodically[0].replace(tzinfo=timezone.utc) + \
|
|
timedelta(minutes=timezone_offset)
|
|
if period_type == 'hourly':
|
|
current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S')
|
|
elif period_type == 'daily':
|
|
current_datetime = current_datetime_local.strftime('%Y-%m-%d')
|
|
elif period_type == '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_shopfloor_periodically[1] is None \
|
|
else row_shopfloor_periodically[1]
|
|
reporting[energy_category_id]['values_actual'].append(actual_value)
|
|
reporting[energy_category_id]['subtotal_actual'] += actual_value
|
|
reporting[energy_category_id]['subtotal_in_kgce_actual'] += actual_value * kgce
|
|
reporting[energy_category_id]['subtotal_in_kgco2e_actual'] += actual_value * kgco2e
|
|
|
|
# calculate reporting period's energy savings
|
|
for i in range(len(reporting[energy_category_id]['values_baseline'])):
|
|
reporting[energy_category_id]['values_saving'].append(
|
|
reporting[energy_category_id]['values_baseline'][i] -
|
|
reporting[energy_category_id]['values_actual'][i])
|
|
|
|
reporting[energy_category_id]['subtotal_saving'] = \
|
|
reporting[energy_category_id]['subtotal_baseline'] - \
|
|
reporting[energy_category_id]['subtotal_actual']
|
|
reporting[energy_category_id]['subtotal_in_kgce_saving'] = \
|
|
reporting[energy_category_id]['subtotal_in_kgce_baseline'] - \
|
|
reporting[energy_category_id]['subtotal_in_kgce_actual']
|
|
reporting[energy_category_id]['subtotal_in_kgco2e_saving'] = \
|
|
reporting[energy_category_id]['subtotal_in_kgco2e_baseline'] - \
|
|
reporting[energy_category_id]['subtotal_in_kgco2e_actual']
|
|
################################################################################################################
|
|
# Step 8: query tariff data
|
|
################################################################################################################
|
|
parameters_data = dict()
|
|
parameters_data['names'] = list()
|
|
parameters_data['timestamps'] = list()
|
|
parameters_data['values'] = list()
|
|
if energy_category_set is not None and len(energy_category_set) > 0:
|
|
for energy_category_id in energy_category_set:
|
|
energy_category_tariff_dict = utilities.get_energy_category_tariffs(shopfloor['cost_center_id'],
|
|
energy_category_id,
|
|
reporting_start_datetime_utc,
|
|
reporting_end_datetime_utc)
|
|
tariff_timestamp_list = list()
|
|
tariff_value_list = list()
|
|
for k, v in energy_category_tariff_dict.items():
|
|
# convert k from utc to local
|
|
k = k + timedelta(minutes=timezone_offset)
|
|
tariff_timestamp_list.append(k.isoformat()[0:19][0:19])
|
|
tariff_value_list.append(v)
|
|
|
|
parameters_data['names'].append('TARIFF-' + energy_category_dict[energy_category_id]['name'])
|
|
parameters_data['timestamps'].append(tariff_timestamp_list)
|
|
parameters_data['values'].append(tariff_value_list)
|
|
|
|
################################################################################################################
|
|
# Step 9: query associated sensors and points data
|
|
################################################################################################################
|
|
for point in point_list:
|
|
point_values = []
|
|
point_timestamps = []
|
|
if point['object_type'] == 'ANALOG_VALUE':
|
|
query = (" SELECT utc_date_time, actual_value "
|
|
" FROM tbl_analog_value "
|
|
" WHERE point_id = %s "
|
|
" AND utc_date_time BETWEEN %s AND %s "
|
|
" ORDER BY utc_date_time ")
|
|
cursor_historical.execute(query, (point['id'],
|
|
reporting_start_datetime_utc,
|
|
reporting_end_datetime_utc))
|
|
rows = cursor_historical.fetchall()
|
|
|
|
if rows is not None and len(rows) > 0:
|
|
for row in rows:
|
|
current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \
|
|
timedelta(minutes=timezone_offset)
|
|
current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S')
|
|
point_timestamps.append(current_datetime)
|
|
point_values.append(row[1])
|
|
|
|
elif point['object_type'] == 'ENERGY_VALUE':
|
|
query = (" SELECT utc_date_time, actual_value "
|
|
" FROM tbl_energy_value "
|
|
" WHERE point_id = %s "
|
|
" AND utc_date_time BETWEEN %s AND %s "
|
|
" ORDER BY utc_date_time ")
|
|
cursor_historical.execute(query, (point['id'],
|
|
reporting_start_datetime_utc,
|
|
reporting_end_datetime_utc))
|
|
rows = cursor_historical.fetchall()
|
|
|
|
if rows is not None and len(rows) > 0:
|
|
for row in rows:
|
|
current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \
|
|
timedelta(minutes=timezone_offset)
|
|
current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S')
|
|
point_timestamps.append(current_datetime)
|
|
point_values.append(row[1])
|
|
elif point['object_type'] == 'DIGITAL_VALUE':
|
|
query = (" SELECT utc_date_time, actual_value "
|
|
" FROM tbl_digital_value "
|
|
" WHERE point_id = %s "
|
|
" AND utc_date_time BETWEEN %s AND %s "
|
|
" ORDER BY utc_date_time ")
|
|
cursor_historical.execute(query, (point['id'],
|
|
reporting_start_datetime_utc,
|
|
reporting_end_datetime_utc))
|
|
rows = cursor_historical.fetchall()
|
|
|
|
if rows is not None and len(rows) > 0:
|
|
for row in rows:
|
|
current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \
|
|
timedelta(minutes=timezone_offset)
|
|
current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S')
|
|
point_timestamps.append(current_datetime)
|
|
point_values.append(row[1])
|
|
|
|
parameters_data['names'].append(point['name'] + ' (' + point['units'] + ')')
|
|
parameters_data['timestamps'].append(point_timestamps)
|
|
parameters_data['values'].append(point_values)
|
|
|
|
################################################################################################################
|
|
# Step 10: construct the report
|
|
################################################################################################################
|
|
if cursor_system:
|
|
cursor_system.close()
|
|
if cnx_system:
|
|
cnx_system.disconnect()
|
|
|
|
if cursor_energy:
|
|
cursor_energy.close()
|
|
if cnx_energy:
|
|
cnx_energy.disconnect()
|
|
|
|
if cursor_energy_baseline:
|
|
cursor_energy_baseline.close()
|
|
if cnx_energy_baseline:
|
|
cnx_energy_baseline.disconnect()
|
|
|
|
if cursor_historical:
|
|
cursor_historical.close()
|
|
if cnx_historical:
|
|
cnx_historical.disconnect()
|
|
|
|
result = dict()
|
|
|
|
result['shopfloor'] = dict()
|
|
result['shopfloor']['name'] = shopfloor['name']
|
|
result['shopfloor']['area'] = shopfloor['area']
|
|
|
|
result['base_period'] = dict()
|
|
result['base_period']['names'] = list()
|
|
result['base_period']['units'] = list()
|
|
result['base_period']['timestamps'] = list()
|
|
result['base_period']['values_saving'] = list()
|
|
result['base_period']['subtotals_saving'] = list()
|
|
result['base_period']['subtotals_in_kgce_saving'] = list()
|
|
result['base_period']['subtotals_in_kgco2e_saving'] = list()
|
|
result['base_period']['total_in_kgce_saving'] = Decimal(0.0)
|
|
result['base_period']['total_in_kgco2e_saving'] = Decimal(0.0)
|
|
if energy_category_set is not None and len(energy_category_set) > 0:
|
|
for energy_category_id in energy_category_set:
|
|
result['base_period']['names'].append(energy_category_dict[energy_category_id]['name'])
|
|
result['base_period']['units'].append(energy_category_dict[energy_category_id]['unit_of_measure'])
|
|
result['base_period']['timestamps'].append(base[energy_category_id]['timestamps'])
|
|
result['base_period']['values_saving'].append(base[energy_category_id]['values_saving'])
|
|
result['base_period']['subtotals_saving'].append(base[energy_category_id]['subtotal_saving'])
|
|
result['base_period']['subtotals_in_kgce_saving'].append(
|
|
base[energy_category_id]['subtotal_in_kgce_saving'])
|
|
result['base_period']['subtotals_in_kgco2e_saving'].append(
|
|
base[energy_category_id]['subtotal_in_kgco2e_saving'])
|
|
result['base_period']['total_in_kgce_saving'] += base[energy_category_id]['subtotal_in_kgce_saving']
|
|
result['base_period']['total_in_kgco2e_saving'] += base[energy_category_id]['subtotal_in_kgco2e_saving']
|
|
|
|
result['reporting_period'] = dict()
|
|
result['reporting_period']['names'] = list()
|
|
result['reporting_period']['energy_category_ids'] = list()
|
|
result['reporting_period']['units'] = list()
|
|
result['reporting_period']['timestamps'] = list()
|
|
result['reporting_period']['values_saving'] = list()
|
|
result['reporting_period']['subtotals_saving'] = list()
|
|
result['reporting_period']['subtotals_in_kgce_saving'] = list()
|
|
result['reporting_period']['subtotals_in_kgco2e_saving'] = list()
|
|
result['reporting_period']['subtotals_per_unit_area_saving'] = list()
|
|
result['reporting_period']['increment_rates_saving'] = list()
|
|
result['reporting_period']['total_in_kgce_saving'] = Decimal(0.0)
|
|
result['reporting_period']['total_in_kgco2e_saving'] = Decimal(0.0)
|
|
result['reporting_period']['increment_rate_in_kgce_saving'] = Decimal(0.0)
|
|
result['reporting_period']['increment_rate_in_kgco2e_saving'] = Decimal(0.0)
|
|
|
|
if energy_category_set is not None and len(energy_category_set) > 0:
|
|
for energy_category_id in energy_category_set:
|
|
result['reporting_period']['names'].append(energy_category_dict[energy_category_id]['name'])
|
|
result['reporting_period']['energy_category_ids'].append(energy_category_id)
|
|
result['reporting_period']['units'].append(energy_category_dict[energy_category_id]['unit_of_measure'])
|
|
result['reporting_period']['timestamps'].append(reporting[energy_category_id]['timestamps'])
|
|
result['reporting_period']['values_saving'].append(reporting[energy_category_id]['values_saving'])
|
|
result['reporting_period']['subtotals_saving'].append(reporting[energy_category_id]['subtotal_saving'])
|
|
result['reporting_period']['subtotals_in_kgce_saving'].append(
|
|
reporting[energy_category_id]['subtotal_in_kgce_saving'])
|
|
result['reporting_period']['subtotals_in_kgco2e_saving'].append(
|
|
reporting[energy_category_id]['subtotal_in_kgco2e_saving'])
|
|
result['reporting_period']['subtotals_per_unit_area_saving'].append(
|
|
reporting[energy_category_id]['subtotal_saving'] / shopfloor['area'] if shopfloor['area'] > 0.0
|
|
else None)
|
|
result['reporting_period']['increment_rates_saving'].append(
|
|
(reporting[energy_category_id]['subtotal_saving'] - base[energy_category_id]['subtotal_saving']) /
|
|
base[energy_category_id]['subtotal_saving']
|
|
if base[energy_category_id]['subtotal_saving'] > 0.0 else None)
|
|
result['reporting_period']['total_in_kgce_saving'] += \
|
|
reporting[energy_category_id]['subtotal_in_kgce_saving']
|
|
result['reporting_period']['total_in_kgco2e_saving'] += \
|
|
reporting[energy_category_id]['subtotal_in_kgco2e_saving']
|
|
|
|
result['reporting_period']['total_in_kgco2e_per_unit_area_saving'] = \
|
|
result['reporting_period']['total_in_kgce_saving'] / shopfloor['area'] if shopfloor['area'] > 0.0 else None
|
|
|
|
result['reporting_period']['increment_rate_in_kgce_saving'] = \
|
|
(result['reporting_period']['total_in_kgce_saving'] - result['base_period']['total_in_kgce_saving']) / \
|
|
result['base_period']['total_in_kgce_saving'] \
|
|
if result['base_period']['total_in_kgce_saving'] > Decimal(0.0) else None
|
|
|
|
result['reporting_period']['total_in_kgce_per_unit_area_saving'] = \
|
|
result['reporting_period']['total_in_kgco2e_saving'] / shopfloor['area'] \
|
|
if shopfloor['area'] > 0.0 else None
|
|
|
|
result['reporting_period']['increment_rate_in_kgco2e_saving'] = \
|
|
(result['reporting_period']['total_in_kgco2e_saving'] - result['base_period']['total_in_kgco2e_saving']) / \
|
|
result['base_period']['total_in_kgco2e_saving'] \
|
|
if result['base_period']['total_in_kgco2e_saving'] > Decimal(0.0) else None
|
|
|
|
result['parameters'] = {
|
|
"names": parameters_data['names'],
|
|
"timestamps": parameters_data['timestamps'],
|
|
"values": parameters_data['values']
|
|
}
|
|
|
|
result['excel_bytes_base64'] = excelexporters.shopfloorsaving.export(result,
|
|
shopfloor['name'],
|
|
reporting_start_datetime_local,
|
|
reporting_end_datetime_local,
|
|
period_type)
|
|
|
|
resp.text = json.dumps(result)
|