MyEMS /
myems
| Total Complexity | 122 |
| Total Lines | 616 |
| Duplicated Lines | 98.05 % |
| Changes | 0 | ||
Duplicate code is one of the most pungent code smells. A rule that is often used is to re-structure code once it is duplicated in three or more places.
Common duplication problems, and corresponding solutions are:
Complex classes like reports.combinedequipmentcarbon often do a lot of different things. To break such a class down, we need to identify a cohesive component within that class. A common approach to find such a component is to look for fields/methods that share the same prefixes, or suffixes.
Once you have determined the fields that belong together, you can apply the Extract Class refactoring. If the component makes sense as a sub-class, Extract Subclass is also a candidate, and is often faster.
| 1 | import re |
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| 2 | import falcon |
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| 3 | import simplejson as json |
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| 4 | import mysql.connector |
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| 5 | import config |
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| 6 | from datetime import datetime, timedelta, timezone |
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| 7 | from core import utilities |
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| 8 | from decimal import Decimal |
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| 9 | import excelexporters.combinedequipmentcarbon |
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| 10 | |||
| 11 | |||
| 12 | View Code Duplication | class Reporting: |
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Duplication
introduced
by
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| 13 | @staticmethod |
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| 14 | def __init__(): |
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| 15 | """"Initializes Reporting""" |
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| 16 | pass |
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| 17 | |||
| 18 | @staticmethod |
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| 19 | def on_options(req, resp): |
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| 20 | resp.status = falcon.HTTP_200 |
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| 21 | |||
| 22 | #################################################################################################################### |
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| 23 | # PROCEDURES |
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| 24 | # Step 1: valid parameters |
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| 25 | # Step 2: query the combined equipment |
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| 26 | # Step 3: query energy items |
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| 27 | # Step 4: query associated points |
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| 28 | # Step 5: query associated equipments |
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| 29 | # Step 6: query base period energy carbon dioxide emissions |
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| 30 | # Step 7: query reporting period energy carbon dioxide emissions |
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| 31 | # Step 8: query tariff data |
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| 32 | # Step 9: query associated points data |
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| 33 | # Step 10: query associated equipments energy carbon dioxide emissions |
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| 34 | # Step 11: construct the report |
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| 35 | #################################################################################################################### |
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| 36 | @staticmethod |
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| 37 | def on_get(req, resp): |
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| 38 | print(req.params) |
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| 39 | combined_equipment_id = req.params.get('combinedequipmentid') |
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| 40 | combined_equipment_uuid = req.params.get('combinedequipmentuuid') |
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| 41 | period_type = req.params.get('periodtype') |
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| 42 | base_start_datetime_local = req.params.get('baseperiodstartdatetime') |
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| 43 | base_end_datetime_local = req.params.get('baseperiodenddatetime') |
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| 44 | reporting_start_datetime_local = req.params.get('reportingperiodstartdatetime') |
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| 45 | reporting_end_datetime_local = req.params.get('reportingperiodenddatetime') |
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| 46 | |||
| 47 | ################################################################################################################ |
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| 48 | # Step 1: valid parameters |
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| 49 | ################################################################################################################ |
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| 50 | if combined_equipment_id is None and combined_equipment_uuid is None: |
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| 51 | raise falcon.HTTPError(falcon.HTTP_400, |
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| 52 | title='API.BAD_REQUEST', |
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| 53 | description='API.INVALID_COMBINED_EQUIPMENT_ID') |
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| 54 | |||
| 55 | if combined_equipment_id is not None: |
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| 56 | combined_equipment_id = str.strip(combined_equipment_id) |
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| 57 | if not combined_equipment_id.isdigit() or int(combined_equipment_id) <= 0: |
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| 58 | raise falcon.HTTPError(falcon.HTTP_400, |
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| 59 | title='API.BAD_REQUEST', |
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| 60 | description='API.INVALID_COMBINED_EQUIPMENT_ID') |
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| 61 | |||
| 62 | if combined_equipment_uuid is not None: |
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| 63 | 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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| 64 | match = regex.match(str.strip(combined_equipment_uuid)) |
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| 65 | if not bool(match): |
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| 66 | raise falcon.HTTPError(falcon.HTTP_400, |
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| 67 | title='API.BAD_REQUEST', |
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| 68 | description='API.INVALID_COMBINED_EQUIPMENT_UUID') |
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| 69 | |||
| 70 | if period_type is None: |
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| 71 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_PERIOD_TYPE') |
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| 72 | else: |
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| 73 | period_type = str.strip(period_type) |
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| 74 | if period_type not in ['hourly', 'daily', 'weekly', 'monthly', 'yearly']: |
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| 75 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_PERIOD_TYPE') |
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| 76 | |||
| 77 | timezone_offset = int(config.utc_offset[1:3]) * 60 + int(config.utc_offset[4:6]) |
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| 78 | if config.utc_offset[0] == '-': |
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| 79 | timezone_offset = -timezone_offset |
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| 80 | |||
| 81 | base_start_datetime_utc = None |
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| 82 | if base_start_datetime_local is not None and len(str.strip(base_start_datetime_local)) > 0: |
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| 83 | base_start_datetime_local = str.strip(base_start_datetime_local) |
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| 84 | try: |
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| 85 | base_start_datetime_utc = datetime.strptime(base_start_datetime_local, |
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| 86 | '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ |
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| 87 | timedelta(minutes=timezone_offset) |
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| 88 | except ValueError: |
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| 89 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 90 | description="API.INVALID_BASE_PERIOD_START_DATETIME") |
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| 91 | |||
| 92 | base_end_datetime_utc = None |
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| 93 | if base_end_datetime_local is not None and len(str.strip(base_end_datetime_local)) > 0: |
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| 94 | base_end_datetime_local = str.strip(base_end_datetime_local) |
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| 95 | try: |
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| 96 | base_end_datetime_utc = datetime.strptime(base_end_datetime_local, |
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| 97 | '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ |
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| 98 | timedelta(minutes=timezone_offset) |
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| 99 | except ValueError: |
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| 100 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 101 | description="API.INVALID_BASE_PERIOD_END_DATETIME") |
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| 102 | |||
| 103 | if base_start_datetime_utc is not None and base_end_datetime_utc is not None and \ |
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| 104 | base_start_datetime_utc >= base_end_datetime_utc: |
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| 105 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 106 | description='API.INVALID_BASE_PERIOD_END_DATETIME') |
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| 107 | |||
| 108 | if reporting_start_datetime_local is None: |
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| 109 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 110 | description="API.INVALID_REPORTING_PERIOD_START_DATETIME") |
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| 111 | else: |
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| 112 | reporting_start_datetime_local = str.strip(reporting_start_datetime_local) |
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| 113 | try: |
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| 114 | reporting_start_datetime_utc = datetime.strptime(reporting_start_datetime_local, |
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| 115 | '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ |
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| 116 | timedelta(minutes=timezone_offset) |
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| 117 | except ValueError: |
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| 118 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 119 | description="API.INVALID_REPORTING_PERIOD_START_DATETIME") |
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| 120 | |||
| 121 | if reporting_end_datetime_local is None: |
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| 122 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 123 | description="API.INVALID_REPORTING_PERIOD_END_DATETIME") |
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| 124 | else: |
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| 125 | reporting_end_datetime_local = str.strip(reporting_end_datetime_local) |
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| 126 | try: |
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| 127 | reporting_end_datetime_utc = datetime.strptime(reporting_end_datetime_local, |
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| 128 | '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ |
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| 129 | timedelta(minutes=timezone_offset) |
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| 130 | except ValueError: |
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| 131 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 132 | description="API.INVALID_REPORTING_PERIOD_END_DATETIME") |
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| 133 | |||
| 134 | if reporting_start_datetime_utc >= reporting_end_datetime_utc: |
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| 135 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 136 | description='API.INVALID_REPORTING_PERIOD_END_DATETIME') |
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| 137 | |||
| 138 | ################################################################################################################ |
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| 139 | # Step 2: query the combined equipment |
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| 140 | ################################################################################################################ |
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| 141 | cnx_system = mysql.connector.connect(**config.myems_system_db) |
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| 142 | cursor_system = cnx_system.cursor() |
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| 143 | |||
| 144 | cnx_carbon = mysql.connector.connect(**config.myems_carbon_db) |
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| 145 | cursor_carbon = cnx_carbon.cursor() |
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| 146 | |||
| 147 | cnx_historical = mysql.connector.connect(**config.myems_historical_db) |
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| 148 | cursor_historical = cnx_historical.cursor() |
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| 149 | |||
| 150 | if combined_equipment_id is not None: |
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| 151 | cursor_system.execute(" SELECT id, name, cost_center_id " |
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| 152 | " FROM tbl_combined_equipments " |
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| 153 | " WHERE id = %s ", (combined_equipment_id,)) |
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| 154 | row_combined_equipment = cursor_system.fetchone() |
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| 155 | elif combined_equipment_uuid is not None: |
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| 156 | cursor_system.execute(" SELECT id, name, cost_center_id " |
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| 157 | " FROM tbl_combined_equipments " |
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| 158 | " WHERE uuid = %s ", (combined_equipment_uuid,)) |
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| 159 | row_combined_equipment = cursor_system.fetchone() |
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| 160 | |||
| 161 | if row_combined_equipment is None: |
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| 162 | if cursor_system: |
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| 163 | cursor_system.close() |
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| 164 | if cnx_system: |
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| 165 | cnx_system.close() |
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| 166 | |||
| 167 | if cursor_carbon: |
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| 168 | cursor_carbon.close() |
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| 169 | if cnx_carbon: |
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| 170 | cnx_carbon.close() |
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| 171 | |||
| 172 | if cursor_historical: |
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| 173 | cursor_historical.close() |
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| 174 | if cnx_historical: |
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| 175 | cnx_historical.close() |
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| 176 | raise falcon.HTTPError(falcon.HTTP_404, |
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| 177 | title='API.NOT_FOUND', |
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| 178 | description='API.COMBINED_EQUIPMENT_NOT_FOUND') |
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| 179 | |||
| 180 | combined_equipment = dict() |
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| 181 | combined_equipment['id'] = row_combined_equipment[0] |
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| 182 | combined_equipment['name'] = row_combined_equipment[1] |
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| 183 | combined_equipment['cost_center_id'] = row_combined_equipment[2] |
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| 184 | |||
| 185 | ################################################################################################################ |
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| 186 | # Step 3: query energy categories |
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| 187 | ################################################################################################################ |
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| 188 | energy_category_set = set() |
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| 189 | # query energy categories in base period |
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| 190 | cursor_carbon.execute(" SELECT DISTINCT(energy_category_id) " |
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| 191 | " FROM tbl_combined_equipment_input_category_hourly " |
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| 192 | " WHERE combined_equipment_id = %s " |
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| 193 | " AND start_datetime_utc >= %s " |
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| 194 | " AND start_datetime_utc < %s ", |
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| 195 | (combined_equipment['id'], base_start_datetime_utc, base_end_datetime_utc)) |
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| 196 | rows_energy_categories = cursor_carbon.fetchall() |
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| 197 | if rows_energy_categories is not None or len(rows_energy_categories) > 0: |
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| 198 | for row_energy_category in rows_energy_categories: |
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| 199 | energy_category_set.add(row_energy_category[0]) |
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| 200 | |||
| 201 | # query energy categories in reporting period |
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| 202 | cursor_carbon.execute(" SELECT DISTINCT(energy_category_id) " |
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| 203 | " FROM tbl_combined_equipment_input_category_hourly " |
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| 204 | " WHERE combined_equipment_id = %s " |
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| 205 | " AND start_datetime_utc >= %s " |
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| 206 | " AND start_datetime_utc < %s ", |
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| 207 | (combined_equipment['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) |
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| 208 | rows_energy_categories = cursor_carbon.fetchall() |
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| 209 | if rows_energy_categories is not None or len(rows_energy_categories) > 0: |
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| 210 | for row_energy_category in rows_energy_categories: |
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| 211 | energy_category_set.add(row_energy_category[0]) |
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| 212 | |||
| 213 | # query all energy categories in base period and reporting period |
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| 214 | cursor_system.execute(" SELECT id, name, unit_of_measure, kgce, kgco2e " |
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| 215 | " FROM tbl_energy_categories " |
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| 216 | " ORDER BY id ", ) |
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| 217 | rows_energy_categories = cursor_system.fetchall() |
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| 218 | if rows_energy_categories is None or len(rows_energy_categories) == 0: |
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| 219 | if cursor_system: |
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| 220 | cursor_system.close() |
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| 221 | if cnx_system: |
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| 222 | cnx_system.close() |
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| 223 | |||
| 224 | if cursor_carbon: |
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| 225 | cursor_carbon.close() |
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| 226 | if cnx_carbon: |
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| 227 | cnx_carbon.close() |
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| 228 | |||
| 229 | if cursor_historical: |
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| 230 | cursor_historical.close() |
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| 231 | if cnx_historical: |
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| 232 | cnx_historical.close() |
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| 233 | raise falcon.HTTPError(falcon.HTTP_404, |
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| 234 | title='API.NOT_FOUND', |
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| 235 | description='API.ENERGY_CATEGORY_NOT_FOUND') |
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| 236 | energy_category_dict = dict() |
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| 237 | for row_energy_category in rows_energy_categories: |
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| 238 | if row_energy_category[0] in energy_category_set: |
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| 239 | energy_category_dict[row_energy_category[0]] = {"name": row_energy_category[1], |
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| 240 | "unit_of_measure": row_energy_category[2], |
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| 241 | "kgce": row_energy_category[3], |
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| 242 | "kgco2e": row_energy_category[4]} |
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| 243 | |||
| 244 | ################################################################################################################ |
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| 245 | # Step 4: query associated points |
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| 246 | ################################################################################################################ |
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| 247 | point_list = list() |
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| 248 | cursor_system.execute(" SELECT p.id, ep.name, p.units, p.object_type " |
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| 249 | " FROM tbl_combined_equipments e, tbl_combined_equipments_parameters ep, tbl_points p " |
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| 250 | " WHERE e.id = %s AND e.id = ep.combined_equipment_id AND ep.parameter_type = 'point' " |
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| 251 | " AND ep.point_id = p.id " |
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| 252 | " ORDER BY p.id ", (combined_equipment['id'],)) |
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| 253 | rows_points = cursor_system.fetchall() |
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| 254 | if rows_points is not None and len(rows_points) > 0: |
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| 255 | for row in rows_points: |
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| 256 | point_list.append({"id": row[0], "name": row[1], "units": row[2], "object_type": row[3]}) |
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| 257 | |||
| 258 | ################################################################################################################ |
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| 259 | # Step 5: query associated equipments |
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| 260 | ################################################################################################################ |
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| 261 | associated_equipment_list = list() |
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| 262 | cursor_system.execute(" SELECT e.id, e.name " |
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| 263 | " FROM tbl_equipments e,tbl_combined_equipments_equipments ee" |
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| 264 | " WHERE ee.combined_equipment_id = %s AND e.id = ee.equipment_id" |
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| 265 | " ORDER BY id ", (combined_equipment['id'],)) |
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| 266 | rows_associated_equipments = cursor_system.fetchall() |
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| 267 | if rows_associated_equipments is not None and len(rows_associated_equipments) > 0: |
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| 268 | for row in rows_associated_equipments: |
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| 269 | associated_equipment_list.append({"id": row[0], "name": row[1]}) |
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| 270 | |||
| 271 | ################################################################################################################ |
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| 272 | # Step 6: query base period energy carbon dioxide emissions |
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| 273 | ################################################################################################################ |
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| 274 | base = dict() |
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| 275 | if energy_category_set is not None and len(energy_category_set) > 0: |
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| 276 | for energy_category_id in energy_category_set: |
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| 277 | base[energy_category_id] = dict() |
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| 278 | base[energy_category_id]['timestamps'] = list() |
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| 279 | base[energy_category_id]['values'] = list() |
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| 280 | base[energy_category_id]['subtotal'] = Decimal(0.0) |
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| 281 | |||
| 282 | cursor_carbon.execute(" SELECT start_datetime_utc, actual_value " |
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| 283 | " FROM tbl_combined_equipment_input_category_hourly " |
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| 284 | " WHERE combined_equipment_id = %s " |
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| 285 | " AND energy_category_id = %s " |
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| 286 | " AND start_datetime_utc >= %s " |
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| 287 | " AND start_datetime_utc < %s " |
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| 288 | " ORDER BY start_datetime_utc ", |
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| 289 | (combined_equipment['id'], |
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| 290 | energy_category_id, |
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| 291 | base_start_datetime_utc, |
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| 292 | base_end_datetime_utc)) |
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| 293 | rows_combined_equipment_hourly = cursor_carbon.fetchall() |
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| 294 | |||
| 295 | rows_combined_equipment_periodically = \ |
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| 296 | utilities.aggregate_hourly_data_by_period(rows_combined_equipment_hourly, |
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| 297 | base_start_datetime_utc, |
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| 298 | base_end_datetime_utc, |
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| 299 | period_type) |
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| 300 | for row_combined_equipment_periodically in rows_combined_equipment_periodically: |
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| 301 | current_datetime_local = row_combined_equipment_periodically[0].replace(tzinfo=timezone.utc) + \ |
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| 302 | timedelta(minutes=timezone_offset) |
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| 303 | if period_type == 'hourly': |
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| 304 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
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| 305 | elif period_type == 'daily': |
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| 306 | current_datetime = current_datetime_local.strftime('%Y-%m-%d') |
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| 307 | elif period_type == 'weekly': |
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| 308 | current_datetime = current_datetime_local.strftime('%Y-%m-%d') |
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| 309 | elif period_type == 'monthly': |
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| 310 | current_datetime = current_datetime_local.strftime('%Y-%m') |
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| 311 | elif period_type == 'yearly': |
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| 312 | current_datetime = current_datetime_local.strftime('%Y') |
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| 313 | |||
| 314 | actual_value = Decimal(0.0) if row_combined_equipment_periodically[1] is None \ |
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| 315 | else row_combined_equipment_periodically[1] |
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| 316 | base[energy_category_id]['timestamps'].append(current_datetime) |
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| 317 | base[energy_category_id]['values'].append(actual_value) |
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| 318 | base[energy_category_id]['subtotal'] += actual_value |
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| 319 | |||
| 320 | ################################################################################################################ |
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| 321 | # Step 7: query reporting period energy carbon dioxide emissions |
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| 322 | ################################################################################################################ |
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| 323 | reporting = dict() |
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| 324 | if energy_category_set is not None and len(energy_category_set) > 0: |
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| 325 | for energy_category_id in energy_category_set: |
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| 326 | reporting[energy_category_id] = dict() |
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| 327 | reporting[energy_category_id]['timestamps'] = list() |
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| 328 | reporting[energy_category_id]['values'] = list() |
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| 329 | reporting[energy_category_id]['subtotal'] = Decimal(0.0) |
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| 330 | reporting[energy_category_id]['toppeak'] = Decimal(0.0) |
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| 331 | reporting[energy_category_id]['onpeak'] = Decimal(0.0) |
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| 332 | reporting[energy_category_id]['midpeak'] = Decimal(0.0) |
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| 333 | reporting[energy_category_id]['offpeak'] = Decimal(0.0) |
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| 334 | |||
| 335 | cursor_carbon.execute(" SELECT start_datetime_utc, actual_value " |
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| 336 | " FROM tbl_combined_equipment_input_category_hourly " |
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| 337 | " WHERE combined_equipment_id = %s " |
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| 338 | " AND energy_category_id = %s " |
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| 339 | " AND start_datetime_utc >= %s " |
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| 340 | " AND start_datetime_utc < %s " |
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| 341 | " ORDER BY start_datetime_utc ", |
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| 342 | (combined_equipment['id'], |
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| 343 | energy_category_id, |
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| 344 | reporting_start_datetime_utc, |
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| 345 | reporting_end_datetime_utc)) |
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| 346 | rows_combined_equipment_hourly = cursor_carbon.fetchall() |
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| 347 | |||
| 348 | rows_combined_equipment_periodically = \ |
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| 349 | utilities.aggregate_hourly_data_by_period(rows_combined_equipment_hourly, |
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| 350 | reporting_start_datetime_utc, |
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| 351 | reporting_end_datetime_utc, |
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| 352 | period_type) |
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| 353 | for row_combined_equipment_periodically in rows_combined_equipment_periodically: |
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| 354 | current_datetime_local = row_combined_equipment_periodically[0].replace(tzinfo=timezone.utc) + \ |
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| 355 | timedelta(minutes=timezone_offset) |
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| 356 | if period_type == 'hourly': |
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| 357 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
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| 358 | elif period_type == 'daily': |
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| 359 | current_datetime = current_datetime_local.strftime('%Y-%m-%d') |
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| 360 | elif period_type == 'weekly': |
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| 361 | current_datetime = current_datetime_local.strftime('%Y-%m-%d') |
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| 362 | elif period_type == 'monthly': |
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| 363 | current_datetime = current_datetime_local.strftime('%Y-%m') |
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| 364 | elif period_type == 'yearly': |
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| 365 | current_datetime = current_datetime_local.strftime('%Y') |
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| 366 | |||
| 367 | actual_value = Decimal(0.0) if row_combined_equipment_periodically[1] is None \ |
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| 368 | else row_combined_equipment_periodically[1] |
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| 369 | reporting[energy_category_id]['timestamps'].append(current_datetime) |
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| 370 | reporting[energy_category_id]['values'].append(actual_value) |
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| 371 | reporting[energy_category_id]['subtotal'] += actual_value |
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| 372 | |||
| 373 | energy_category_tariff_dict = \ |
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| 374 | utilities.get_energy_category_peak_types(combined_equipment['cost_center_id'], |
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| 375 | energy_category_id, |
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| 376 | reporting_start_datetime_utc, |
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| 377 | reporting_end_datetime_utc) |
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| 378 | for row in rows_combined_equipment_hourly: |
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| 379 | peak_type = energy_category_tariff_dict.get(row[0], None) |
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| 380 | if peak_type == 'toppeak': |
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| 381 | reporting[energy_category_id]['toppeak'] += row[1] |
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| 382 | elif peak_type == 'onpeak': |
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| 383 | reporting[energy_category_id]['onpeak'] += row[1] |
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| 384 | elif peak_type == 'midpeak': |
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| 385 | reporting[energy_category_id]['midpeak'] += row[1] |
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| 386 | elif peak_type == 'offpeak': |
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| 387 | reporting[energy_category_id]['offpeak'] += row[1] |
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| 388 | |||
| 389 | ################################################################################################################ |
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| 390 | # Step 8: query tariff data |
||
| 391 | ################################################################################################################ |
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| 392 | parameters_data = dict() |
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| 393 | parameters_data['names'] = list() |
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| 394 | parameters_data['timestamps'] = list() |
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| 395 | parameters_data['values'] = list() |
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| 396 | if energy_category_set is not None and len(energy_category_set) > 0: |
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| 397 | for energy_category_id in energy_category_set: |
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| 398 | energy_category_tariff_dict = \ |
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| 399 | utilities.get_energy_category_tariffs(combined_equipment['cost_center_id'], |
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| 400 | energy_category_id, |
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| 401 | reporting_start_datetime_utc, |
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| 402 | reporting_end_datetime_utc) |
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| 403 | tariff_timestamp_list = list() |
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| 404 | tariff_value_list = list() |
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| 405 | for k, v in energy_category_tariff_dict.items(): |
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| 406 | # convert k from utc to local |
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| 407 | k = k + timedelta(minutes=timezone_offset) |
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| 408 | tariff_timestamp_list.append(k.isoformat()[0:19][0:19]) |
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| 409 | tariff_value_list.append(v) |
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| 410 | |||
| 411 | parameters_data['names'].append('TARIFF-' + energy_category_dict[energy_category_id]['name']) |
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| 412 | parameters_data['timestamps'].append(tariff_timestamp_list) |
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| 413 | parameters_data['values'].append(tariff_value_list) |
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| 414 | |||
| 415 | ################################################################################################################ |
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| 416 | # Step 9: query associated points data |
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| 417 | ################################################################################################################ |
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| 418 | for point in point_list: |
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| 419 | point_values = [] |
||
| 420 | point_timestamps = [] |
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| 421 | if point['object_type'] == 'ANALOG_VALUE': |
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| 422 | query = (" SELECT utc_date_time, actual_value " |
||
| 423 | " FROM tbl_analog_value " |
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| 424 | " WHERE point_id = %s " |
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| 425 | " AND utc_date_time BETWEEN %s AND %s " |
||
| 426 | " ORDER BY utc_date_time ") |
||
| 427 | cursor_historical.execute(query, (point['id'], |
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| 428 | reporting_start_datetime_utc, |
||
| 429 | reporting_end_datetime_utc)) |
||
| 430 | rows = cursor_historical.fetchall() |
||
| 431 | |||
| 432 | if rows is not None and len(rows) > 0: |
||
| 433 | for row in rows: |
||
| 434 | current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ |
||
| 435 | timedelta(minutes=timezone_offset) |
||
| 436 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
||
| 437 | point_timestamps.append(current_datetime) |
||
| 438 | point_values.append(row[1]) |
||
| 439 | |||
| 440 | elif point['object_type'] == 'ENERGY_VALUE': |
||
| 441 | query = (" SELECT utc_date_time, actual_value " |
||
| 442 | " FROM tbl_energy_value " |
||
| 443 | " WHERE point_id = %s " |
||
| 444 | " AND utc_date_time BETWEEN %s AND %s " |
||
| 445 | " ORDER BY utc_date_time ") |
||
| 446 | cursor_historical.execute(query, (point['id'], |
||
| 447 | reporting_start_datetime_utc, |
||
| 448 | reporting_end_datetime_utc)) |
||
| 449 | rows = cursor_historical.fetchall() |
||
| 450 | |||
| 451 | if rows is not None and len(rows) > 0: |
||
| 452 | for row in rows: |
||
| 453 | current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ |
||
| 454 | timedelta(minutes=timezone_offset) |
||
| 455 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
||
| 456 | point_timestamps.append(current_datetime) |
||
| 457 | point_values.append(row[1]) |
||
| 458 | elif point['object_type'] == 'DIGITAL_VALUE': |
||
| 459 | query = (" SELECT utc_date_time, actual_value " |
||
| 460 | " FROM tbl_digital_value " |
||
| 461 | " WHERE point_id = %s " |
||
| 462 | " AND utc_date_time BETWEEN %s AND %s " |
||
| 463 | " ORDER BY utc_date_time ") |
||
| 464 | cursor_historical.execute(query, (point['id'], |
||
| 465 | reporting_start_datetime_utc, |
||
| 466 | reporting_end_datetime_utc)) |
||
| 467 | rows = cursor_historical.fetchall() |
||
| 468 | |||
| 469 | if rows is not None and len(rows) > 0: |
||
| 470 | for row in rows: |
||
| 471 | current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ |
||
| 472 | timedelta(minutes=timezone_offset) |
||
| 473 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
||
| 474 | point_timestamps.append(current_datetime) |
||
| 475 | point_values.append(row[1]) |
||
| 476 | |||
| 477 | parameters_data['names'].append(point['name'] + ' (' + point['units'] + ')') |
||
| 478 | parameters_data['timestamps'].append(point_timestamps) |
||
| 479 | parameters_data['values'].append(point_values) |
||
| 480 | |||
| 481 | ################################################################################################################ |
||
| 482 | # Step 10: query associated equipments energy carbon dioxide emissions |
||
| 483 | ################################################################################################################ |
||
| 484 | associated_equipment_data = dict() |
||
| 485 | |||
| 486 | if energy_category_set is not None and len(energy_category_set) > 0: |
||
| 487 | for energy_category_id in energy_category_set: |
||
| 488 | associated_equipment_data[energy_category_id] = dict() |
||
| 489 | associated_equipment_data[energy_category_id]['associated_equipment_names'] = list() |
||
| 490 | associated_equipment_data[energy_category_id]['subtotals'] = list() |
||
| 491 | for associated_equipment in associated_equipment_list: |
||
| 492 | associated_equipment_data[energy_category_id]['associated_equipment_names'].append( |
||
| 493 | associated_equipment['name']) |
||
| 494 | |||
| 495 | cursor_carbon.execute(" SELECT SUM(actual_value) " |
||
| 496 | " FROM tbl_equipment_input_category_hourly " |
||
| 497 | " WHERE equipment_id = %s " |
||
| 498 | " AND energy_category_id = %s " |
||
| 499 | " AND start_datetime_utc >= %s " |
||
| 500 | " AND start_datetime_utc < %s ", |
||
| 501 | (associated_equipment['id'], |
||
| 502 | energy_category_id, |
||
| 503 | reporting_start_datetime_utc, |
||
| 504 | reporting_end_datetime_utc)) |
||
| 505 | row_subtotal = cursor_carbon.fetchone() |
||
| 506 | |||
| 507 | subtotal = Decimal(0.0) if (row_subtotal is None or row_subtotal[0] is None) else row_subtotal[0] |
||
| 508 | associated_equipment_data[energy_category_id]['subtotals'].append(subtotal) |
||
| 509 | |||
| 510 | ################################################################################################################ |
||
| 511 | # Step 11: construct the report |
||
| 512 | ################################################################################################################ |
||
| 513 | if cursor_system: |
||
| 514 | cursor_system.close() |
||
| 515 | if cnx_system: |
||
| 516 | cnx_system.close() |
||
| 517 | |||
| 518 | if cursor_carbon: |
||
| 519 | cursor_carbon.close() |
||
| 520 | if cnx_carbon: |
||
| 521 | cnx_carbon.close() |
||
| 522 | |||
| 523 | if cursor_historical: |
||
| 524 | cursor_historical.close() |
||
| 525 | if cnx_historical: |
||
| 526 | cnx_historical.close() |
||
| 527 | |||
| 528 | result = dict() |
||
| 529 | |||
| 530 | result['combined_equipment'] = dict() |
||
| 531 | result['combined_equipment']['name'] = combined_equipment['name'] |
||
| 532 | |||
| 533 | result['base_period'] = dict() |
||
| 534 | result['base_period']['names'] = list() |
||
| 535 | result['base_period']['units'] = list() |
||
| 536 | result['base_period']['timestamps'] = list() |
||
| 537 | result['base_period']['values'] = list() |
||
| 538 | result['base_period']['subtotals'] = list() |
||
| 539 | result['base_period']['total'] = Decimal(0.0) |
||
| 540 | if energy_category_set is not None and len(energy_category_set) > 0: |
||
| 541 | for energy_category_id in energy_category_set: |
||
| 542 | result['base_period']['names'].append(energy_category_dict[energy_category_id]['name']) |
||
| 543 | result['base_period']['units'].append('KG') |
||
| 544 | result['base_period']['timestamps'].append(base[energy_category_id]['timestamps']) |
||
| 545 | result['base_period']['values'].append(base[energy_category_id]['values']) |
||
| 546 | result['base_period']['subtotals'].append(base[energy_category_id]['subtotal']) |
||
| 547 | result['base_period']['total'] += base[energy_category_id]['subtotal'] |
||
| 548 | |||
| 549 | result['reporting_period'] = dict() |
||
| 550 | result['reporting_period']['names'] = list() |
||
| 551 | result['reporting_period']['energy_category_ids'] = list() |
||
| 552 | result['reporting_period']['units'] = list() |
||
| 553 | result['reporting_period']['timestamps'] = list() |
||
| 554 | result['reporting_period']['values'] = list() |
||
| 555 | result['reporting_period']['subtotals'] = list() |
||
| 556 | result['reporting_period']['toppeaks'] = list() |
||
| 557 | result['reporting_period']['onpeaks'] = list() |
||
| 558 | result['reporting_period']['midpeaks'] = list() |
||
| 559 | result['reporting_period']['offpeaks'] = list() |
||
| 560 | result['reporting_period']['increment_rates'] = list() |
||
| 561 | result['reporting_period']['total'] = Decimal(0.0) |
||
| 562 | result['reporting_period']['total_increment_rate'] = Decimal(0.0) |
||
| 563 | result['reporting_period']['total_unit'] = 'KG' |
||
| 564 | |||
| 565 | if energy_category_set is not None and len(energy_category_set) > 0: |
||
| 566 | for energy_category_id in energy_category_set: |
||
| 567 | result['reporting_period']['names'].append(energy_category_dict[energy_category_id]['name']) |
||
| 568 | result['reporting_period']['energy_category_ids'].append(energy_category_id) |
||
| 569 | result['reporting_period']['units'].append('KG') |
||
| 570 | result['reporting_period']['timestamps'].append(reporting[energy_category_id]['timestamps']) |
||
| 571 | result['reporting_period']['values'].append(reporting[energy_category_id]['values']) |
||
| 572 | result['reporting_period']['subtotals'].append(reporting[energy_category_id]['subtotal']) |
||
| 573 | result['reporting_period']['toppeaks'].append(reporting[energy_category_id]['toppeak']) |
||
| 574 | result['reporting_period']['onpeaks'].append(reporting[energy_category_id]['onpeak']) |
||
| 575 | result['reporting_period']['midpeaks'].append(reporting[energy_category_id]['midpeak']) |
||
| 576 | result['reporting_period']['offpeaks'].append(reporting[energy_category_id]['offpeak']) |
||
| 577 | result['reporting_period']['increment_rates'].append( |
||
| 578 | (reporting[energy_category_id]['subtotal'] - base[energy_category_id]['subtotal']) / |
||
| 579 | base[energy_category_id]['subtotal'] |
||
| 580 | if base[energy_category_id]['subtotal'] > 0.0 else None) |
||
| 581 | result['reporting_period']['total'] += reporting[energy_category_id]['subtotal'] |
||
| 582 | |||
| 583 | result['reporting_period']['total_increment_rate'] = \ |
||
| 584 | (result['reporting_period']['total'] - result['base_period']['total']) / result['base_period']['total'] \ |
||
| 585 | if result['base_period']['total'] > Decimal(0.0) else None |
||
| 586 | |||
| 587 | result['parameters'] = { |
||
| 588 | "names": parameters_data['names'], |
||
| 589 | "timestamps": parameters_data['timestamps'], |
||
| 590 | "values": parameters_data['values'] |
||
| 591 | } |
||
| 592 | |||
| 593 | result['associated_equipment'] = dict() |
||
| 594 | result['associated_equipment']['energy_category_names'] = list() |
||
| 595 | result['associated_equipment']['units'] = list() |
||
| 596 | result['associated_equipment']['associated_equipment_names_array'] = list() |
||
| 597 | result['associated_equipment']['subtotals_array'] = list() |
||
| 598 | result['associated_equipment']['total_unit'] = 'KG' |
||
| 599 | if energy_category_set is not None and len(energy_category_set) > 0: |
||
| 600 | for energy_category_id in energy_category_set: |
||
| 601 | result['associated_equipment']['energy_category_names'].append( |
||
| 602 | energy_category_dict[energy_category_id]['name']) |
||
| 603 | result['associated_equipment']['units'].append('KG') |
||
| 604 | result['associated_equipment']['associated_equipment_names_array'].append( |
||
| 605 | associated_equipment_data[energy_category_id]['associated_equipment_names']) |
||
| 606 | result['associated_equipment']['subtotals_array'].append( |
||
| 607 | associated_equipment_data[energy_category_id]['subtotals']) |
||
| 608 | |||
| 609 | # export result to Excel file and then encode the file to base64 string |
||
| 610 | result['excel_bytes_base64'] = excelexporters.combinedequipmentcarbon.export(result, |
||
| 611 | combined_equipment['name'], |
||
| 612 | reporting_start_datetime_local, |
||
| 613 | reporting_end_datetime_local, |
||
| 614 | period_type) |
||
| 615 | resp.text = json.dumps(result) |
||
| 616 |
Loading history...