myems /
myems-api
| Total Complexity | 97 |
| Total Lines | 520 |
| Duplicated Lines | 98.08 % |
| 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.equipmentload 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 falcon |
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| 2 | import simplejson as json |
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| 3 | import mysql.connector |
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| 4 | import config |
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| 5 | from datetime import datetime, timedelta, timezone |
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| 6 | from core import utilities |
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| 7 | from decimal import Decimal |
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| 8 | |||
| 9 | |||
| 10 | View Code Duplication | class Reporting: |
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Duplication
introduced
by
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| 11 | @staticmethod |
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| 12 | def __init__(): |
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| 13 | pass |
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| 14 | |||
| 15 | @staticmethod |
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| 16 | def on_options(req, resp): |
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| 17 | resp.status = falcon.HTTP_200 |
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| 18 | |||
| 19 | #################################################################################################################### |
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| 20 | # PROCEDURES |
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| 21 | # Step 1: valid parameters |
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| 22 | # Step 2: query the equipment |
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| 23 | # Step 3: query energy categories |
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| 24 | # Step 4: query associated points |
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| 25 | # Step 5: query base period energy input |
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| 26 | # Step 6: query reporting period energy input |
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| 27 | # Step 7: query tariff data |
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| 28 | # Step 8: query associated points data |
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| 29 | # Step 9: construct the report |
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| 30 | #################################################################################################################### |
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| 31 | @staticmethod |
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| 32 | def on_get(req, resp): |
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| 33 | print(req.params) |
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| 34 | equipment_id = req.params.get('equipmentid') |
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| 35 | period_type = req.params.get('periodtype') |
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| 36 | base_start_datetime_local = req.params.get('baseperiodstartdatetime') |
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| 37 | base_end_datetime_local = req.params.get('baseperiodenddatetime') |
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| 38 | reporting_start_datetime_local = req.params.get('reportingperiodstartdatetime') |
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| 39 | reporting_end_datetime_local = req.params.get('reportingperiodenddatetime') |
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| 40 | |||
| 41 | ################################################################################################################ |
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| 42 | # Step 1: valid parameters |
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| 43 | ################################################################################################################ |
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| 44 | if equipment_id is None: |
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| 45 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_EQUIPMENT_ID') |
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| 46 | else: |
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| 47 | equipment_id = str.strip(equipment_id) |
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| 48 | if not equipment_id.isdigit() or int(equipment_id) <= 0: |
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| 49 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_equipment_ID') |
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| 50 | |||
| 51 | if period_type is None: |
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| 52 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_PERIOD_TYPE') |
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| 53 | else: |
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| 54 | period_type = str.strip(period_type) |
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| 55 | if period_type not in ['hourly', 'daily', 'monthly', 'yearly']: |
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| 56 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_PERIOD_TYPE') |
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| 57 | |||
| 58 | timezone_offset = int(config.utc_offset[1:3]) * 60 + int(config.utc_offset[4:6]) |
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| 59 | if config.utc_offset[0] == '-': |
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| 60 | timezone_offset = -timezone_offset |
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| 61 | |||
| 62 | base_start_datetime_utc = None |
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| 63 | if base_start_datetime_local is not None and len(str.strip(base_start_datetime_local)) > 0: |
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| 64 | base_start_datetime_local = str.strip(base_start_datetime_local) |
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| 65 | try: |
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| 66 | base_start_datetime_utc = datetime.strptime(base_start_datetime_local, |
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| 67 | '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ |
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| 68 | timedelta(minutes=timezone_offset) |
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| 69 | except ValueError: |
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| 70 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 71 | description="API.INVALID_BASE_PERIOD_START_DATETIME") |
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| 72 | |||
| 73 | base_end_datetime_utc = None |
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| 74 | if base_end_datetime_local is not None and len(str.strip(base_end_datetime_local)) > 0: |
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| 75 | base_end_datetime_local = str.strip(base_end_datetime_local) |
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| 76 | try: |
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| 77 | base_end_datetime_utc = datetime.strptime(base_end_datetime_local, |
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| 78 | '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ |
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| 79 | timedelta(minutes=timezone_offset) |
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| 80 | except ValueError: |
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| 81 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 82 | description="API.INVALID_BASE_PERIOD_END_DATETIME") |
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| 83 | |||
| 84 | if base_start_datetime_utc is not None and base_end_datetime_utc is not None and \ |
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| 85 | base_start_datetime_utc >= base_end_datetime_utc: |
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| 86 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 87 | description='API.INVALID_BASE_PERIOD_END_DATETIME') |
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| 88 | |||
| 89 | if reporting_start_datetime_local is None: |
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| 90 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 91 | description="API.INVALID_REPORTING_PERIOD_START_DATETIME") |
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| 92 | else: |
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| 93 | reporting_start_datetime_local = str.strip(reporting_start_datetime_local) |
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| 94 | try: |
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| 95 | reporting_start_datetime_utc = datetime.strptime(reporting_start_datetime_local, |
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| 96 | '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ |
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| 97 | timedelta(minutes=timezone_offset) |
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| 98 | except ValueError: |
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| 99 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 100 | description="API.INVALID_REPORTING_PERIOD_START_DATETIME") |
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| 101 | |||
| 102 | if reporting_end_datetime_local is None: |
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| 103 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 104 | description="API.INVALID_REPORTING_PERIOD_END_DATETIME") |
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| 105 | else: |
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| 106 | reporting_end_datetime_local = str.strip(reporting_end_datetime_local) |
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| 107 | try: |
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| 108 | reporting_end_datetime_utc = datetime.strptime(reporting_end_datetime_local, |
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| 109 | '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ |
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| 110 | timedelta(minutes=timezone_offset) |
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| 111 | except ValueError: |
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| 112 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 113 | description="API.INVALID_REPORTING_PERIOD_END_DATETIME") |
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| 114 | |||
| 115 | if reporting_start_datetime_utc >= reporting_end_datetime_utc: |
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| 116 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 117 | description='API.INVALID_REPORTING_PERIOD_END_DATETIME') |
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| 118 | |||
| 119 | ################################################################################################################ |
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| 120 | # Step 2: query the equipment |
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| 121 | ################################################################################################################ |
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| 122 | cnx_system = mysql.connector.connect(**config.myems_system_db) |
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| 123 | cursor_system = cnx_system.cursor() |
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| 124 | |||
| 125 | cnx_energy = mysql.connector.connect(**config.myems_energy_db) |
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| 126 | cursor_energy = cnx_energy.cursor() |
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| 127 | |||
| 128 | cnx_historical = mysql.connector.connect(**config.myems_historical_db) |
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| 129 | cursor_historical = cnx_historical.cursor() |
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| 130 | |||
| 131 | cursor_system.execute(" SELECT id, name, cost_center_id " |
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| 132 | " FROM tbl_equipments " |
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| 133 | " WHERE id = %s ", (equipment_id,)) |
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| 134 | row_equipment = cursor_system.fetchone() |
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| 135 | if row_equipment is None: |
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| 136 | if cursor_system: |
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| 137 | cursor_system.close() |
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| 138 | if cnx_system: |
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| 139 | cnx_system.disconnect() |
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| 140 | |||
| 141 | if cursor_energy: |
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| 142 | cursor_energy.close() |
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| 143 | if cnx_energy: |
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| 144 | cnx_energy.disconnect() |
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| 145 | |||
| 146 | if cnx_historical: |
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| 147 | cnx_historical.close() |
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| 148 | if cursor_historical: |
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| 149 | cursor_historical.disconnect() |
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| 150 | raise falcon.HTTPError(falcon.HTTP_404, title='API.NOT_FOUND', description='API.EQUIPMENT_NOT_FOUND') |
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| 151 | |||
| 152 | equipment = dict() |
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| 153 | equipment['id'] = row_equipment[0] |
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| 154 | equipment['name'] = row_equipment[1] |
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| 155 | equipment['cost_center_id'] = row_equipment[2] |
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| 156 | |||
| 157 | ################################################################################################################ |
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| 158 | # Step 3: query energy categories |
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| 159 | ################################################################################################################ |
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| 160 | energy_category_set = set() |
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| 161 | # query energy categories in base period |
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| 162 | cursor_energy.execute(" SELECT DISTINCT(energy_category_id) " |
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| 163 | " FROM tbl_equipment_input_category_hourly " |
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| 164 | " WHERE equipment_id = %s " |
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| 165 | " AND start_datetime_utc >= %s " |
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| 166 | " AND start_datetime_utc < %s ", |
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| 167 | (equipment['id'], base_start_datetime_utc, base_end_datetime_utc)) |
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| 168 | rows_energy_categories = cursor_energy.fetchall() |
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| 169 | if rows_energy_categories is not None or len(rows_energy_categories) > 0: |
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| 170 | for row_energy_category in rows_energy_categories: |
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| 171 | energy_category_set.add(row_energy_category[0]) |
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| 172 | |||
| 173 | # query energy categories in reporting period |
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| 174 | cursor_energy.execute(" SELECT DISTINCT(energy_category_id) " |
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| 175 | " FROM tbl_equipment_input_category_hourly " |
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| 176 | " WHERE equipment_id = %s " |
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| 177 | " AND start_datetime_utc >= %s " |
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| 178 | " AND start_datetime_utc < %s ", |
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| 179 | (equipment['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) |
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| 180 | rows_energy_categories = cursor_energy.fetchall() |
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| 181 | if rows_energy_categories is not None or len(rows_energy_categories) > 0: |
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| 182 | for row_energy_category in rows_energy_categories: |
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| 183 | energy_category_set.add(row_energy_category[0]) |
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| 184 | |||
| 185 | # query all energy categories in base period and reporting period |
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| 186 | cursor_system.execute(" SELECT id, name, unit_of_measure, kgce, kgco2e " |
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| 187 | " FROM tbl_energy_categories " |
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| 188 | " ORDER BY id ", ) |
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| 189 | rows_energy_categories = cursor_system.fetchall() |
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| 190 | if rows_energy_categories is None or len(rows_energy_categories) == 0: |
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| 191 | if cursor_system: |
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| 192 | cursor_system.close() |
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| 193 | if cnx_system: |
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| 194 | cnx_system.disconnect() |
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| 195 | |||
| 196 | if cursor_energy: |
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| 197 | cursor_energy.close() |
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| 198 | if cnx_energy: |
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| 199 | cnx_energy.disconnect() |
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| 200 | |||
| 201 | if cnx_historical: |
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| 202 | cnx_historical.close() |
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| 203 | if cursor_historical: |
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| 204 | cursor_historical.disconnect() |
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| 205 | raise falcon.HTTPError(falcon.HTTP_404, |
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| 206 | title='API.NOT_FOUND', |
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| 207 | description='API.ENERGY_CATEGORY_NOT_FOUND') |
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| 208 | energy_category_dict = dict() |
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| 209 | for row_energy_category in rows_energy_categories: |
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| 210 | if row_energy_category[0] in energy_category_set: |
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| 211 | energy_category_dict[row_energy_category[0]] = {"name": row_energy_category[1], |
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| 212 | "unit_of_measure": row_energy_category[2], |
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| 213 | "kgce": row_energy_category[3], |
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| 214 | "kgco2e": row_energy_category[4]} |
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| 215 | |||
| 216 | ################################################################################################################ |
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| 217 | # Step 4: query associated points |
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| 218 | ################################################################################################################ |
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| 219 | point_list = list() |
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| 220 | cursor_system.execute(" SELECT p.id, p.name, p.units, p.object_type " |
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| 221 | " FROM tbl_equipments e, tbl_equipments_parameters ep, tbl_points p " |
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| 222 | " WHERE e.id = %s AND e.id = ep.equipment_id AND ep.parameter_type = 'point' " |
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| 223 | " AND ep.point_id = p.id " |
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| 224 | " ORDER BY p.id ", (equipment['id'],)) |
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| 225 | rows_points = cursor_system.fetchall() |
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| 226 | if rows_points is not None and len(rows_points) > 0: |
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| 227 | for row in rows_points: |
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| 228 | point_list.append({"id": row[0], "name": row[1], "units": row[2], "object_type": row[3]}) |
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| 229 | |||
| 230 | ################################################################################################################ |
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| 231 | # Step 6: query base period energy input |
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| 232 | ################################################################################################################ |
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| 233 | base = dict() |
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| 234 | if energy_category_set is not None and len(energy_category_set) > 0: |
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| 235 | for energy_category_id in energy_category_set: |
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| 236 | base[energy_category_id] = dict() |
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| 237 | base[energy_category_id]['timestamps'] = list() |
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| 238 | base[energy_category_id]['sub_averages'] = list() |
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| 239 | base[energy_category_id]['sub_maximums'] = list() |
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| 240 | base[energy_category_id]['average'] = None |
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| 241 | base[energy_category_id]['maximum'] = None |
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| 242 | base[energy_category_id]['factor'] = None |
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| 243 | |||
| 244 | cursor_energy.execute(" SELECT start_datetime_utc, actual_value " |
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| 245 | " FROM tbl_equipment_input_category_hourly " |
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| 246 | " WHERE equipment_id = %s " |
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| 247 | " AND energy_category_id = %s " |
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| 248 | " AND start_datetime_utc >= %s " |
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| 249 | " AND start_datetime_utc < %s " |
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| 250 | " ORDER BY start_datetime_utc ", |
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| 251 | (equipment['id'], |
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| 252 | energy_category_id, |
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| 253 | base_start_datetime_utc, |
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| 254 | base_end_datetime_utc)) |
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| 255 | rows_equipment_hourly = cursor_energy.fetchall() |
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| 256 | |||
| 257 | rows_equipment_periodically, \ |
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| 258 | base[energy_category_id]['average'], \ |
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| 259 | base[energy_category_id]['maximum'] = \ |
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| 260 | utilities.averaging_hourly_data_by_period(rows_equipment_hourly, |
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| 261 | base_start_datetime_utc, |
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| 262 | base_end_datetime_utc, |
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| 263 | period_type) |
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| 264 | base[energy_category_id]['factor'] = \ |
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| 265 | (base[energy_category_id]['average'] / base[energy_category_id]['maximum'] |
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| 266 | if (base[energy_category_id]['average'] is not None and |
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| 267 | base[energy_category_id]['maximum'] is not None and |
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| 268 | base[energy_category_id]['maximum'] > Decimal(0.0)) |
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| 269 | else None) |
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| 270 | |||
| 271 | for row_equipment_periodically in rows_equipment_periodically: |
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| 272 | current_datetime_local = row_equipment_periodically[0].replace(tzinfo=timezone.utc) + \ |
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| 273 | timedelta(minutes=timezone_offset) |
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| 274 | if period_type == 'hourly': |
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| 275 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
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| 276 | elif period_type == 'daily': |
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| 277 | current_datetime = current_datetime_local.strftime('%Y-%m-%d') |
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| 278 | elif period_type == 'monthly': |
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| 279 | current_datetime = current_datetime_local.strftime('%Y-%m') |
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| 280 | elif period_type == 'yearly': |
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| 281 | current_datetime = current_datetime_local.strftime('%Y') |
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| 282 | |||
| 283 | base[energy_category_id]['timestamps'].append(current_datetime) |
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| 284 | base[energy_category_id]['sub_averages'].append(row_equipment_periodically[1]) |
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| 285 | base[energy_category_id]['sub_maximums'].append(row_equipment_periodically[2]) |
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| 286 | |||
| 287 | ################################################################################################################ |
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| 288 | # Step 7: query reporting period energy input |
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| 289 | ################################################################################################################ |
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| 290 | reporting = dict() |
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| 291 | if energy_category_set is not None and len(energy_category_set) > 0: |
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| 292 | for energy_category_id in energy_category_set: |
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| 293 | reporting[energy_category_id] = dict() |
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| 294 | reporting[energy_category_id]['timestamps'] = list() |
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| 295 | reporting[energy_category_id]['sub_averages'] = list() |
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| 296 | reporting[energy_category_id]['sub_maximums'] = list() |
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| 297 | reporting[energy_category_id]['average'] = None |
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| 298 | reporting[energy_category_id]['maximum'] = None |
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| 299 | reporting[energy_category_id]['factor'] = None |
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| 300 | |||
| 301 | cursor_energy.execute(" SELECT start_datetime_utc, actual_value " |
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| 302 | " FROM tbl_equipment_input_category_hourly " |
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| 303 | " WHERE equipment_id = %s " |
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| 304 | " AND energy_category_id = %s " |
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| 305 | " AND start_datetime_utc >= %s " |
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| 306 | " AND start_datetime_utc < %s " |
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| 307 | " ORDER BY start_datetime_utc ", |
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| 308 | (equipment['id'], |
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| 309 | energy_category_id, |
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| 310 | reporting_start_datetime_utc, |
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| 311 | reporting_end_datetime_utc)) |
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| 312 | rows_equipment_hourly = cursor_energy.fetchall() |
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| 313 | |||
| 314 | rows_equipment_periodically, \ |
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| 315 | reporting[energy_category_id]['average'], \ |
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| 316 | reporting[energy_category_id]['maximum'] = \ |
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| 317 | utilities.averaging_hourly_data_by_period(rows_equipment_hourly, |
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| 318 | reporting_start_datetime_utc, |
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| 319 | reporting_end_datetime_utc, |
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| 320 | period_type) |
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| 321 | reporting[energy_category_id]['factor'] = \ |
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| 322 | (reporting[energy_category_id]['average'] / reporting[energy_category_id]['maximum'] |
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| 323 | if (reporting[energy_category_id]['average'] is not None and |
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| 324 | reporting[energy_category_id]['maximum'] is not None and |
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| 325 | reporting[energy_category_id]['maximum'] > Decimal(0.0)) |
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| 326 | else None) |
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| 327 | |||
| 328 | for row_equipment_periodically in rows_equipment_periodically: |
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| 329 | current_datetime_local = row_equipment_periodically[0].replace(tzinfo=timezone.utc) + \ |
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| 330 | timedelta(minutes=timezone_offset) |
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| 331 | if period_type == 'hourly': |
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| 332 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
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| 333 | elif period_type == 'daily': |
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| 334 | current_datetime = current_datetime_local.strftime('%Y-%m-%d') |
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| 335 | elif period_type == 'monthly': |
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| 336 | current_datetime = current_datetime_local.strftime('%Y-%m') |
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| 337 | elif period_type == 'yearly': |
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| 338 | current_datetime = current_datetime_local.strftime('%Y') |
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| 339 | |||
| 340 | reporting[energy_category_id]['timestamps'].append(current_datetime) |
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| 341 | reporting[energy_category_id]['sub_averages'].append(row_equipment_periodically[1]) |
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| 342 | reporting[energy_category_id]['sub_maximums'].append(row_equipment_periodically[2]) |
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| 343 | |||
| 344 | ################################################################################################################ |
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| 345 | # Step 8: query tariff data |
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| 346 | ################################################################################################################ |
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| 347 | parameters_data = dict() |
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| 348 | parameters_data['names'] = list() |
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| 349 | parameters_data['timestamps'] = list() |
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| 350 | parameters_data['values'] = list() |
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| 351 | if energy_category_set is not None and len(energy_category_set) > 0: |
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| 352 | for energy_category_id in energy_category_set: |
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| 353 | energy_category_tariff_dict = utilities.get_energy_category_tariffs(equipment['cost_center_id'], |
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| 354 | energy_category_id, |
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| 355 | reporting_start_datetime_utc, |
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| 356 | reporting_end_datetime_utc) |
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| 357 | tariff_timestamp_list = list() |
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| 358 | tariff_value_list = list() |
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| 359 | for k, v in energy_category_tariff_dict.items(): |
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| 360 | # convert k from utc to local |
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| 361 | k = k + timedelta(minutes=timezone_offset) |
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| 362 | tariff_timestamp_list.append(k.isoformat()[0:19][0:19]) |
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| 363 | tariff_value_list.append(v) |
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| 364 | |||
| 365 | parameters_data['names'].append('TARIFF-' + energy_category_dict[energy_category_id]['name']) |
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| 366 | parameters_data['timestamps'].append(tariff_timestamp_list) |
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| 367 | parameters_data['values'].append(tariff_value_list) |
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| 368 | |||
| 369 | ################################################################################################################ |
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| 370 | # Step 9: query associated points data |
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| 371 | ################################################################################################################ |
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| 372 | for point in point_list: |
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| 373 | point_values = [] |
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| 374 | point_timestamps = [] |
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| 375 | if point['object_type'] == 'ANALOG_VALUE': |
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| 376 | query = (" SELECT utc_date_time, actual_value " |
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| 377 | " FROM tbl_analog_value " |
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| 378 | " WHERE point_id = %s " |
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| 379 | " AND utc_date_time BETWEEN %s AND %s " |
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| 380 | " ORDER BY utc_date_time ") |
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| 381 | cursor_historical.execute(query, (point['id'], |
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| 382 | reporting_start_datetime_utc, |
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| 383 | reporting_end_datetime_utc)) |
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| 384 | rows = cursor_historical.fetchall() |
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| 385 | |||
| 386 | if rows is not None and len(rows) > 0: |
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| 387 | for row in rows: |
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| 388 | current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ |
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| 389 | timedelta(minutes=timezone_offset) |
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| 390 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
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| 391 | point_timestamps.append(current_datetime) |
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| 392 | point_values.append(row[1]) |
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| 393 | |||
| 394 | elif point['object_type'] == 'ENERGY_VALUE': |
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| 395 | query = (" SELECT utc_date_time, actual_value " |
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| 396 | " FROM tbl_energy_value " |
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| 397 | " WHERE point_id = %s " |
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| 398 | " AND utc_date_time BETWEEN %s AND %s " |
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| 399 | " ORDER BY utc_date_time ") |
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| 400 | cursor_historical.execute(query, (point['id'], |
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| 401 | reporting_start_datetime_utc, |
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| 402 | reporting_end_datetime_utc)) |
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| 403 | rows = cursor_historical.fetchall() |
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| 404 | |||
| 405 | if rows is not None and len(rows) > 0: |
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| 406 | for row in rows: |
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| 407 | current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ |
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| 408 | timedelta(minutes=timezone_offset) |
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| 409 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
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| 410 | point_timestamps.append(current_datetime) |
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| 411 | point_values.append(row[1]) |
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| 412 | elif point['object_type'] == 'DIGITAL_VALUE': |
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| 413 | query = (" SELECT utc_date_time, actual_value " |
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| 414 | " FROM tbl_digital_value " |
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| 415 | " WHERE point_id = %s " |
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| 416 | " AND utc_date_time BETWEEN %s AND %s ") |
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| 417 | cursor_historical.execute(query, (point['id'], |
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| 418 | reporting_start_datetime_utc, |
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| 419 | reporting_end_datetime_utc)) |
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| 420 | rows = cursor_historical.fetchall() |
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| 421 | |||
| 422 | if rows is not None and len(rows) > 0: |
||
| 423 | for row in rows: |
||
| 424 | current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ |
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| 425 | timedelta(minutes=timezone_offset) |
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| 426 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
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| 427 | point_timestamps.append(current_datetime) |
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| 428 | point_values.append(row[1]) |
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| 429 | |||
| 430 | parameters_data['names'].append(point['name'] + ' (' + point['units'] + ')') |
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| 431 | parameters_data['timestamps'].append(point_timestamps) |
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| 432 | parameters_data['values'].append(point_values) |
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| 433 | |||
| 434 | ################################################################################################################ |
||
| 435 | # Step 10: construct the report |
||
| 436 | ################################################################################################################ |
||
| 437 | if cursor_system: |
||
| 438 | cursor_system.close() |
||
| 439 | if cnx_system: |
||
| 440 | cnx_system.disconnect() |
||
| 441 | |||
| 442 | if cursor_energy: |
||
| 443 | cursor_energy.close() |
||
| 444 | if cnx_energy: |
||
| 445 | cnx_energy.disconnect() |
||
| 446 | |||
| 447 | result = dict() |
||
| 448 | |||
| 449 | result['equipment'] = dict() |
||
| 450 | result['equipment']['name'] = equipment['name'] |
||
| 451 | |||
| 452 | result['base_period'] = dict() |
||
| 453 | result['base_period']['names'] = list() |
||
| 454 | result['base_period']['units'] = list() |
||
| 455 | result['base_period']['timestamps'] = list() |
||
| 456 | result['base_period']['sub_averages'] = list() |
||
| 457 | result['base_period']['sub_maximums'] = list() |
||
| 458 | result['base_period']['averages'] = list() |
||
| 459 | result['base_period']['maximums'] = list() |
||
| 460 | result['base_period']['factors'] = list() |
||
| 461 | if energy_category_set is not None and len(energy_category_set) > 0: |
||
| 462 | for energy_category_id in energy_category_set: |
||
| 463 | result['base_period']['names'].append(energy_category_dict[energy_category_id]['name']) |
||
| 464 | result['base_period']['units'].append(energy_category_dict[energy_category_id]['unit_of_measure']) |
||
| 465 | result['base_period']['timestamps'].append(base[energy_category_id]['timestamps']) |
||
| 466 | result['base_period']['sub_averages'].append(base[energy_category_id]['sub_averages']) |
||
| 467 | result['base_period']['sub_maximums'].append(base[energy_category_id]['sub_maximums']) |
||
| 468 | result['base_period']['averages'].append(base[energy_category_id]['average']) |
||
| 469 | result['base_period']['maximums'].append(base[energy_category_id]['maximum']) |
||
| 470 | result['base_period']['factors'].append(base[energy_category_id]['factor']) |
||
| 471 | |||
| 472 | result['reporting_period'] = dict() |
||
| 473 | result['reporting_period']['names'] = list() |
||
| 474 | result['reporting_period']['energy_category_ids'] = list() |
||
| 475 | result['reporting_period']['units'] = list() |
||
| 476 | result['reporting_period']['timestamps'] = list() |
||
| 477 | result['reporting_period']['sub_averages'] = list() |
||
| 478 | result['reporting_period']['sub_maximums'] = list() |
||
| 479 | result['reporting_period']['averages'] = list() |
||
| 480 | result['reporting_period']['averages_increment_rate'] = list() |
||
| 481 | result['reporting_period']['maximums'] = list() |
||
| 482 | result['reporting_period']['maximums_increment_rate'] = list() |
||
| 483 | result['reporting_period']['factors'] = list() |
||
| 484 | result['reporting_period']['factors_increment_rate'] = list() |
||
| 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 | result['reporting_period']['names'].append(energy_category_dict[energy_category_id]['name']) |
||
| 489 | result['reporting_period']['energy_category_ids'].append(energy_category_id) |
||
| 490 | result['reporting_period']['units'].append(energy_category_dict[energy_category_id]['unit_of_measure']) |
||
| 491 | result['reporting_period']['timestamps'].append(reporting[energy_category_id]['timestamps']) |
||
| 492 | result['reporting_period']['sub_averages'].append(reporting[energy_category_id]['sub_averages']) |
||
| 493 | result['reporting_period']['sub_maximums'].append(reporting[energy_category_id]['sub_maximums']) |
||
| 494 | result['reporting_period']['averages'].append(reporting[energy_category_id]['average']) |
||
| 495 | result['reporting_period']['averages_increment_rate'].append( |
||
| 496 | (reporting[energy_category_id]['average'] - base[energy_category_id]['average']) / |
||
| 497 | base[energy_category_id]['average'] if (base[energy_category_id]['average'] is not None and |
||
| 498 | base[energy_category_id]['average'] > Decimal(0.0)) |
||
| 499 | else None) |
||
| 500 | result['reporting_period']['maximums'].append(reporting[energy_category_id]['maximum']) |
||
| 501 | result['reporting_period']['maximums_increment_rate'].append( |
||
| 502 | (reporting[energy_category_id]['maximum'] - base[energy_category_id]['maximum']) / |
||
| 503 | base[energy_category_id]['maximum'] if (base[energy_category_id]['maximum'] is not None and |
||
| 504 | base[energy_category_id]['maximum'] > Decimal(0.0)) |
||
| 505 | else None) |
||
| 506 | result['reporting_period']['factors'].append(reporting[energy_category_id]['factor']) |
||
| 507 | result['reporting_period']['factors_increment_rate'].append( |
||
| 508 | (reporting[energy_category_id]['factor'] - base[energy_category_id]['factor']) / |
||
| 509 | base[energy_category_id]['factor'] if (base[energy_category_id]['factor'] is not None and |
||
| 510 | base[energy_category_id]['factor'] > Decimal(0.0)) |
||
| 511 | else None) |
||
| 512 | |||
| 513 | result['parameters'] = { |
||
| 514 | "names": parameters_data['names'], |
||
| 515 | "timestamps": parameters_data['timestamps'], |
||
| 516 | "values": parameters_data['values'] |
||
| 517 | } |
||
| 518 | |||
| 519 | resp.body = json.dumps(result) |
||
| 520 |
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