myems /
myems-api
| Conditions | 141 |
| Total Lines | 689 |
| Code Lines | 517 |
| Lines | 689 |
| Ratio | 100 % |
| Changes | 0 | ||
Small methods make your code easier to understand, in particular if combined with a good name. Besides, if your method is small, finding a good name is usually much easier.
For example, if you find yourself adding comments to a method's body, this is usually a good sign to extract the commented part to a new method, and use the comment as a starting point when coming up with a good name for this new method.
Commonly applied refactorings include:
If many parameters/temporary variables are present:
Complex classes like combinedequipmentefficiency.Reporting.on_get() 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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| 33 | @staticmethod |
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| 34 | def on_get(req, resp): |
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| 35 | print(req.params) |
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| 36 | combined_equipment_id = req.params.get('combinedequipmentid') |
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| 37 | period_type = req.params.get('periodtype') |
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| 38 | base_start_datetime_local = req.params.get('baseperiodstartdatetime') |
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| 39 | base_end_datetime_local = req.params.get('baseperiodenddatetime') |
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| 40 | reporting_start_datetime_local = req.params.get('reportingperiodstartdatetime') |
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| 41 | reporting_end_datetime_local = req.params.get('reportingperiodenddatetime') |
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| 42 | |||
| 43 | ################################################################################################################ |
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| 44 | # Step 1: valid parameters |
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| 45 | ################################################################################################################ |
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| 46 | if combined_equipment_id is None: |
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| 47 | raise falcon.HTTPError(falcon.HTTP_400, |
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| 48 | title='API.BAD_REQUEST', |
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| 49 | description='API.INVALID_COMBINED_EQUIPMENT_ID') |
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| 50 | else: |
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| 51 | combined_equipment_id = str.strip(combined_equipment_id) |
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| 52 | if not combined_equipment_id.isdigit() or int(combined_equipment_id) <= 0: |
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| 53 | raise falcon.HTTPError(falcon.HTTP_400, |
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| 54 | title='API.BAD_REQUEST', |
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| 55 | description='API.INVALID_COMBINED_EQUIPMENT_ID') |
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| 56 | |||
| 57 | if period_type is None: |
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| 58 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_PERIOD_TYPE') |
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| 59 | else: |
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| 60 | period_type = str.strip(period_type) |
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| 61 | if period_type not in ['hourly', 'daily', 'monthly', 'yearly']: |
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| 62 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_PERIOD_TYPE') |
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| 63 | |||
| 64 | timezone_offset = int(config.utc_offset[1:3]) * 60 + int(config.utc_offset[4:6]) |
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| 65 | if config.utc_offset[0] == '-': |
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| 66 | timezone_offset = -timezone_offset |
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| 67 | |||
| 68 | base_start_datetime_utc = None |
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| 69 | if base_start_datetime_local is not None and len(str.strip(base_start_datetime_local)) > 0: |
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| 70 | base_start_datetime_local = str.strip(base_start_datetime_local) |
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| 71 | try: |
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| 72 | base_start_datetime_utc = datetime.strptime(base_start_datetime_local, |
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| 73 | '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ |
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| 74 | timedelta(minutes=timezone_offset) |
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| 75 | except ValueError: |
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| 76 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 77 | description="API.INVALID_BASE_PERIOD_BEGINS_DATETIME") |
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| 78 | |||
| 79 | base_end_datetime_utc = None |
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| 80 | if base_end_datetime_local is not None and len(str.strip(base_end_datetime_local)) > 0: |
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| 81 | base_end_datetime_local = str.strip(base_end_datetime_local) |
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| 82 | try: |
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| 83 | base_end_datetime_utc = datetime.strptime(base_end_datetime_local, |
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| 84 | '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ |
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| 85 | timedelta(minutes=timezone_offset) |
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| 86 | except ValueError: |
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| 87 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 88 | description="API.INVALID_BASE_PERIOD_ENDS_DATETIME") |
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| 89 | |||
| 90 | if base_start_datetime_utc is not None and base_end_datetime_utc is not None and \ |
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| 91 | base_start_datetime_utc >= base_end_datetime_utc: |
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| 92 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 93 | description='API.INVALID_BASE_PERIOD_ENDS_DATETIME') |
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| 94 | |||
| 95 | if reporting_start_datetime_local is None: |
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| 96 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 97 | description="API.INVALID_REPORTING_PERIOD_BEGINS_DATETIME") |
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| 98 | else: |
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| 99 | reporting_start_datetime_local = str.strip(reporting_start_datetime_local) |
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| 100 | try: |
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| 101 | reporting_start_datetime_utc = datetime.strptime(reporting_start_datetime_local, |
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| 102 | '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ |
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| 103 | timedelta(minutes=timezone_offset) |
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| 104 | except ValueError: |
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| 105 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 106 | description="API.INVALID_REPORTING_PERIOD_BEGINS_DATETIME") |
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| 107 | |||
| 108 | if reporting_end_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_ENDS_DATETIME") |
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| 111 | else: |
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| 112 | reporting_end_datetime_local = str.strip(reporting_end_datetime_local) |
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| 113 | try: |
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| 114 | reporting_end_datetime_utc = datetime.strptime(reporting_end_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_ENDS_DATETIME") |
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| 120 | |||
| 121 | if reporting_start_datetime_utc >= reporting_end_datetime_utc: |
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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_ENDS_DATETIME') |
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| 124 | |||
| 125 | ################################################################################################################ |
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| 126 | # Step 2: query the combined equipment |
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| 127 | ################################################################################################################ |
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| 128 | cnx_system = mysql.connector.connect(**config.myems_system_db) |
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| 129 | cursor_system = cnx_system.cursor() |
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| 130 | |||
| 131 | cnx_energy = mysql.connector.connect(**config.myems_billing_db) |
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| 132 | cursor_energy = cnx_energy.cursor() |
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| 133 | |||
| 134 | cnx_historical = mysql.connector.connect(**config.myems_historical_db) |
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| 135 | cursor_historical = cnx_historical.cursor() |
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| 136 | |||
| 137 | cursor_system.execute(" SELECT id, name, cost_center_id " |
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| 138 | " FROM tbl_combined_equipments " |
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| 139 | " WHERE id = %s ", (combined_equipment_id,)) |
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| 140 | row_combined_equipment = cursor_system.fetchone() |
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| 141 | if row_combined_equipment is None: |
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| 142 | if cursor_system: |
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| 143 | cursor_system.close() |
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| 144 | if cnx_system: |
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| 145 | cnx_system.disconnect() |
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| 146 | |||
| 147 | if cursor_energy: |
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| 148 | cursor_energy.close() |
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| 149 | if cnx_energy: |
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| 150 | cnx_energy.disconnect() |
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| 151 | |||
| 152 | if cnx_historical: |
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| 153 | cnx_historical.close() |
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| 154 | if cursor_historical: |
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| 155 | cursor_historical.disconnect() |
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| 156 | raise falcon.HTTPError(falcon.HTTP_404, |
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| 157 | title='API.NOT_FOUND', |
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| 158 | description='API.COMBINED_EQUIPMENT_NOT_FOUND') |
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| 159 | |||
| 160 | combined_equipment = dict() |
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| 161 | combined_equipment['id'] = row_combined_equipment[0] |
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| 162 | combined_equipment['name'] = row_combined_equipment[1] |
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| 163 | combined_equipment['cost_center_id'] = row_combined_equipment[2] |
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| 164 | |||
| 165 | ################################################################################################################ |
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| 166 | # Step 3: query input energy categories and output energy categories |
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| 167 | ################################################################################################################ |
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| 168 | energy_category_set_input = set() |
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| 169 | energy_category_set_output = set() |
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| 170 | # query input energy categories in base period |
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| 171 | cursor_energy.execute(" SELECT DISTINCT(energy_category_id) " |
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| 172 | " FROM tbl_combined_equipment_input_category_hourly " |
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| 173 | " WHERE combined_equipment_id = %s " |
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| 174 | " AND start_datetime_utc >= %s " |
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| 175 | " AND start_datetime_utc < %s ", |
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| 176 | (combined_equipment['id'], base_start_datetime_utc, base_end_datetime_utc)) |
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| 177 | rows_energy_categories = cursor_energy.fetchall() |
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| 178 | if rows_energy_categories is not None or len(rows_energy_categories) > 0: |
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| 179 | for row_energy_category in rows_energy_categories: |
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| 180 | energy_category_set_input.add(row_energy_category[0]) |
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| 181 | |||
| 182 | # query input energy categories in reporting period |
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| 183 | cursor_energy.execute(" SELECT DISTINCT(energy_category_id) " |
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| 184 | " FROM tbl_combined_equipment_input_category_hourly " |
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| 185 | " WHERE combined_equipment_id = %s " |
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| 186 | " AND start_datetime_utc >= %s " |
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| 187 | " AND start_datetime_utc < %s ", |
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| 188 | (combined_equipment['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) |
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| 189 | rows_energy_categories = cursor_energy.fetchall() |
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| 190 | if rows_energy_categories is not None or len(rows_energy_categories) > 0: |
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| 191 | for row_energy_category in rows_energy_categories: |
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| 192 | energy_category_set_input.add(row_energy_category[0]) |
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| 193 | |||
| 194 | # query output energy categories in base period |
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| 195 | cursor_energy.execute(" SELECT DISTINCT(energy_category_id) " |
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| 196 | " FROM tbl_combined_equipment_output_category_hourly " |
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| 197 | " WHERE combined_equipment_id = %s " |
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| 198 | " AND start_datetime_utc >= %s " |
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| 199 | " AND start_datetime_utc < %s ", |
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| 200 | (combined_equipment['id'], base_start_datetime_utc, base_end_datetime_utc)) |
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| 201 | rows_energy_categories = cursor_energy.fetchall() |
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| 202 | if rows_energy_categories is not None or len(rows_energy_categories) > 0: |
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| 203 | for row_energy_category in rows_energy_categories: |
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| 204 | energy_category_set_output.add(row_energy_category[0]) |
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| 205 | |||
| 206 | # query output energy categories in reporting period |
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| 207 | cursor_energy.execute(" SELECT DISTINCT(energy_category_id) " |
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| 208 | " FROM tbl_combined_equipment_output_category_hourly " |
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| 209 | " WHERE combined_equipment_id = %s " |
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| 210 | " AND start_datetime_utc >= %s " |
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| 211 | " AND start_datetime_utc < %s ", |
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| 212 | (combined_equipment['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) |
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| 213 | rows_energy_categories = cursor_energy.fetchall() |
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| 214 | if rows_energy_categories is not None or len(rows_energy_categories) > 0: |
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| 215 | for row_energy_category in rows_energy_categories: |
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| 216 | energy_category_set_output.add(row_energy_category[0]) |
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| 217 | |||
| 218 | # query properties of all energy categories above |
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| 219 | cursor_system.execute(" SELECT id, name, unit_of_measure, kgce, kgco2e " |
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| 220 | " FROM tbl_energy_categories " |
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| 221 | " ORDER BY id ", ) |
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| 222 | rows_energy_categories = cursor_system.fetchall() |
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| 223 | if rows_energy_categories is None or len(rows_energy_categories) == 0: |
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| 224 | if cursor_system: |
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| 225 | cursor_system.close() |
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| 226 | if cnx_system: |
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| 227 | cnx_system.disconnect() |
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| 228 | |||
| 229 | if cursor_energy: |
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| 230 | cursor_energy.close() |
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| 231 | if cnx_energy: |
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| 232 | cnx_energy.disconnect() |
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| 233 | |||
| 234 | if cnx_historical: |
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| 235 | cnx_historical.close() |
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| 236 | if cursor_historical: |
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| 237 | cursor_historical.disconnect() |
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| 238 | raise falcon.HTTPError(falcon.HTTP_404, |
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| 239 | title='API.NOT_FOUND', |
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| 240 | description='API.ENERGY_CATEGORY_NOT_FOUND') |
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| 241 | energy_category_dict = dict() |
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| 242 | for row_energy_category in rows_energy_categories: |
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| 243 | if row_energy_category[0] in energy_category_set_input or \ |
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| 244 | row_energy_category[0] in energy_category_set_output: |
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| 245 | energy_category_dict[row_energy_category[0]] = {"name": row_energy_category[1], |
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| 246 | "unit_of_measure": row_energy_category[2], |
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| 247 | "kgce": row_energy_category[3], |
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| 248 | "kgco2e": row_energy_category[4]} |
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| 249 | |||
| 250 | ################################################################################################################ |
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| 251 | # Step 4: query associated points |
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| 252 | ################################################################################################################ |
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| 253 | point_list = list() |
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| 254 | cursor_system.execute(" SELECT p.id, p.name, p.units, p.object_type " |
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| 255 | " FROM tbl_combined_equipments e, tbl_combined_equipments_parameters ep, tbl_points p " |
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| 256 | " WHERE e.id = %s AND e.id = ep.combined_equipment_id AND ep.parameter_type = 'point' " |
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| 257 | " AND ep.point_id = p.id " |
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| 258 | " ORDER BY p.id ", (combined_equipment['id'],)) |
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| 259 | rows_points = cursor_system.fetchall() |
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| 260 | if rows_points is not None and len(rows_points) > 0: |
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| 261 | for row in rows_points: |
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| 262 | point_list.append({"id": row[0], "name": row[1], "units": row[2], "object_type": row[3]}) |
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| 263 | |||
| 264 | ################################################################################################################ |
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| 265 | # Step 5: query base period energy input |
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| 266 | ################################################################################################################ |
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| 267 | base_input = dict() |
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| 268 | if energy_category_set_input is not None and len(energy_category_set_input) > 0: |
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| 269 | for energy_category_id in energy_category_set_input: |
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| 270 | base_input[energy_category_id] = dict() |
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| 271 | base_input[energy_category_id]['timestamps'] = list() |
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| 272 | base_input[energy_category_id]['values'] = list() |
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| 273 | base_input[energy_category_id]['subtotal'] = Decimal(0.0) |
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| 274 | |||
| 275 | cursor_energy.execute(" SELECT start_datetime_utc, actual_value " |
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| 276 | " FROM tbl_combined_equipment_input_category_hourly " |
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| 277 | " WHERE combined_equipment_id = %s " |
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| 278 | " AND energy_category_id = %s " |
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| 279 | " AND start_datetime_utc >= %s " |
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| 280 | " AND start_datetime_utc < %s " |
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| 281 | " ORDER BY start_datetime_utc ", |
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| 282 | (combined_equipment['id'], |
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| 283 | energy_category_id, |
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| 284 | base_start_datetime_utc, |
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| 285 | base_end_datetime_utc)) |
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| 286 | rows_combined_equipment_hourly = cursor_energy.fetchall() |
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| 287 | |||
| 288 | rows_combined_equipment_periodically = \ |
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| 289 | utilities.aggregate_hourly_data_by_period(rows_combined_equipment_hourly, |
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| 290 | base_start_datetime_utc, |
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| 291 | base_end_datetime_utc, |
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| 292 | period_type) |
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| 293 | for row_combined_equipment_periodically in rows_combined_equipment_periodically: |
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| 294 | current_datetime_local = row_combined_equipment_periodically[0].replace(tzinfo=timezone.utc) + \ |
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| 295 | timedelta(minutes=timezone_offset) |
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| 296 | if period_type == 'hourly': |
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| 297 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
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| 298 | elif period_type == 'daily': |
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| 299 | current_datetime = current_datetime_local.strftime('%Y-%m-%d') |
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| 300 | elif period_type == 'monthly': |
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| 301 | current_datetime = current_datetime_local.strftime('%Y-%m') |
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| 302 | elif period_type == 'yearly': |
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| 303 | current_datetime = current_datetime_local.strftime('%Y') |
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| 304 | |||
| 305 | actual_value = Decimal(0.0) if row_combined_equipment_periodically[1] is None \ |
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| 306 | else row_combined_equipment_periodically[1] |
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| 307 | base_input[energy_category_id]['timestamps'].append(current_datetime) |
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| 308 | base_input[energy_category_id]['values'].append(actual_value) |
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| 309 | base_input[energy_category_id]['subtotal'] += actual_value |
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| 310 | |||
| 311 | ################################################################################################################ |
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| 312 | # Step 6: query base period energy output |
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| 313 | ################################################################################################################ |
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| 314 | base_output = dict() |
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| 315 | if energy_category_set_output is not None and len(energy_category_set_output) > 0: |
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| 316 | for energy_category_id in energy_category_set_output: |
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| 317 | base_output[energy_category_id] = dict() |
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| 318 | base_output[energy_category_id]['timestamps'] = list() |
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| 319 | base_output[energy_category_id]['values'] = list() |
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| 320 | base_output[energy_category_id]['subtotal'] = Decimal(0.0) |
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| 321 | |||
| 322 | cursor_energy.execute(" SELECT start_datetime_utc, actual_value " |
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| 323 | " FROM tbl_combined_equipment_output_category_hourly " |
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| 324 | " WHERE combined_equipment_id = %s " |
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| 325 | " AND energy_category_id = %s " |
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| 326 | " AND start_datetime_utc >= %s " |
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| 327 | " AND start_datetime_utc < %s " |
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| 328 | " ORDER BY start_datetime_utc ", |
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| 329 | (combined_equipment['id'], |
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| 330 | energy_category_id, |
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| 331 | base_start_datetime_utc, |
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| 332 | base_end_datetime_utc)) |
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| 333 | rows_combined_equipment_hourly = cursor_energy.fetchall() |
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| 334 | |||
| 335 | rows_combined_equipment_periodically = \ |
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| 336 | utilities.aggregate_hourly_data_by_period(rows_combined_equipment_hourly, |
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| 337 | base_start_datetime_utc, |
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| 338 | base_end_datetime_utc, |
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| 339 | period_type) |
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| 340 | for row_combined_equipment_periodically in rows_combined_equipment_periodically: |
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| 341 | current_datetime_local = row_combined_equipment_periodically[0].replace(tzinfo=timezone.utc) + \ |
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| 342 | timedelta(minutes=timezone_offset) |
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| 343 | if period_type == 'hourly': |
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| 344 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
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| 345 | elif period_type == 'daily': |
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| 346 | current_datetime = current_datetime_local.strftime('%Y-%m-%d') |
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| 347 | elif period_type == 'monthly': |
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| 348 | current_datetime = current_datetime_local.strftime('%Y-%m') |
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| 349 | elif period_type == 'yearly': |
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| 350 | current_datetime = current_datetime_local.strftime('%Y') |
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| 351 | |||
| 352 | actual_value = Decimal(0.0) if row_combined_equipment_periodically[1] is None \ |
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| 353 | else row_combined_equipment_periodically[1] |
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| 354 | base_output[energy_category_id]['timestamps'].append(current_datetime) |
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| 355 | base_output[energy_category_id]['values'].append(actual_value) |
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| 356 | base_output[energy_category_id]['subtotal'] += actual_value |
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| 357 | ################################################################################################################ |
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| 358 | # Step 7: query reporting period energy input |
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| 359 | ################################################################################################################ |
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| 360 | reporting_input = dict() |
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| 361 | if energy_category_set_input is not None and len(energy_category_set_input) > 0: |
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| 362 | for energy_category_id in energy_category_set_input: |
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| 363 | |||
| 364 | reporting_input[energy_category_id] = dict() |
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| 365 | reporting_input[energy_category_id]['timestamps'] = list() |
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| 366 | reporting_input[energy_category_id]['values'] = list() |
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| 367 | reporting_input[energy_category_id]['subtotal'] = Decimal(0.0) |
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| 368 | |||
| 369 | cursor_energy.execute(" SELECT start_datetime_utc, actual_value " |
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| 370 | " FROM tbl_combined_equipment_input_category_hourly " |
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| 371 | " WHERE combined_equipment_id = %s " |
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| 372 | " AND energy_category_id = %s " |
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| 373 | " AND start_datetime_utc >= %s " |
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| 374 | " AND start_datetime_utc < %s " |
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| 375 | " ORDER BY start_datetime_utc ", |
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| 376 | (combined_equipment['id'], |
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| 377 | energy_category_id, |
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| 378 | reporting_start_datetime_utc, |
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| 379 | reporting_end_datetime_utc)) |
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| 380 | rows_combined_equipment_hourly = cursor_energy.fetchall() |
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| 381 | |||
| 382 | rows_combined_equipment_periodically = \ |
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| 383 | utilities.aggregate_hourly_data_by_period(rows_combined_equipment_hourly, |
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| 384 | reporting_start_datetime_utc, |
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| 385 | reporting_end_datetime_utc, |
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| 386 | period_type) |
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| 387 | for row_combined_equipment_periodically in rows_combined_equipment_periodically: |
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| 388 | current_datetime_local = row_combined_equipment_periodically[0].replace(tzinfo=timezone.utc) + \ |
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| 389 | timedelta(minutes=timezone_offset) |
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| 390 | if period_type == 'hourly': |
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| 391 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
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| 392 | elif period_type == 'daily': |
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| 393 | current_datetime = current_datetime_local.strftime('%Y-%m-%d') |
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| 394 | elif period_type == 'monthly': |
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| 395 | current_datetime = current_datetime_local.strftime('%Y-%m') |
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| 396 | elif period_type == 'yearly': |
||
| 397 | current_datetime = current_datetime_local.strftime('%Y') |
||
| 398 | |||
| 399 | actual_value = Decimal(0.0) if row_combined_equipment_periodically[1] is None \ |
||
| 400 | else row_combined_equipment_periodically[1] |
||
| 401 | reporting_input[energy_category_id]['timestamps'].append(current_datetime) |
||
| 402 | reporting_input[energy_category_id]['values'].append(actual_value) |
||
| 403 | reporting_input[energy_category_id]['subtotal'] += actual_value |
||
| 404 | |||
| 405 | ################################################################################################################ |
||
| 406 | # Step 8: query reporting period energy output |
||
| 407 | ################################################################################################################ |
||
| 408 | reporting_output = dict() |
||
| 409 | if energy_category_set_output is not None and len(energy_category_set_output) > 0: |
||
| 410 | for energy_category_id in energy_category_set_output: |
||
| 411 | |||
| 412 | reporting_output[energy_category_id] = dict() |
||
| 413 | reporting_output[energy_category_id]['timestamps'] = list() |
||
| 414 | reporting_output[energy_category_id]['values'] = list() |
||
| 415 | reporting_output[energy_category_id]['subtotal'] = Decimal(0.0) |
||
| 416 | |||
| 417 | cursor_energy.execute(" SELECT start_datetime_utc, actual_value " |
||
| 418 | " FROM tbl_combined_equipment_output_category_hourly " |
||
| 419 | " WHERE combined_equipment_id = %s " |
||
| 420 | " AND energy_category_id = %s " |
||
| 421 | " AND start_datetime_utc >= %s " |
||
| 422 | " AND start_datetime_utc < %s " |
||
| 423 | " ORDER BY start_datetime_utc ", |
||
| 424 | (combined_equipment['id'], |
||
| 425 | energy_category_id, |
||
| 426 | reporting_start_datetime_utc, |
||
| 427 | reporting_end_datetime_utc)) |
||
| 428 | rows_combined_equipment_hourly = cursor_energy.fetchall() |
||
| 429 | |||
| 430 | rows_combined_equipment_periodically = \ |
||
| 431 | utilities.aggregate_hourly_data_by_period(rows_combined_equipment_hourly, |
||
| 432 | reporting_start_datetime_utc, |
||
| 433 | reporting_end_datetime_utc, |
||
| 434 | period_type) |
||
| 435 | for row_combined_equipment_periodically in rows_combined_equipment_periodically: |
||
| 436 | current_datetime_local = row_combined_equipment_periodically[0].replace(tzinfo=timezone.utc) + \ |
||
| 437 | timedelta(minutes=timezone_offset) |
||
| 438 | if period_type == 'hourly': |
||
| 439 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
||
| 440 | elif period_type == 'daily': |
||
| 441 | current_datetime = current_datetime_local.strftime('%Y-%m-%d') |
||
| 442 | elif period_type == 'monthly': |
||
| 443 | current_datetime = current_datetime_local.strftime('%Y-%m') |
||
| 444 | elif period_type == 'yearly': |
||
| 445 | current_datetime = current_datetime_local.strftime('%Y') |
||
| 446 | |||
| 447 | actual_value = Decimal(0.0) if row_combined_equipment_periodically[1] is None \ |
||
| 448 | else row_combined_equipment_periodically[1] |
||
| 449 | reporting_output[energy_category_id]['timestamps'].append(current_datetime) |
||
| 450 | reporting_output[energy_category_id]['values'].append(actual_value) |
||
| 451 | reporting_output[energy_category_id]['subtotal'] += actual_value |
||
| 452 | |||
| 453 | ################################################################################################################ |
||
| 454 | # Step 9: query tariff data |
||
| 455 | ################################################################################################################ |
||
| 456 | parameters_data = dict() |
||
| 457 | parameters_data['names'] = list() |
||
| 458 | parameters_data['timestamps'] = list() |
||
| 459 | parameters_data['values'] = list() |
||
| 460 | if energy_category_set_input is not None and len(energy_category_set_input) > 0: |
||
| 461 | for energy_category_id in energy_category_set_input: |
||
| 462 | energy_category_tariff_dict = utilities.get_energy_category_tariffs(combined_equipment['cost_center_id'], |
||
| 463 | energy_category_id, |
||
| 464 | reporting_start_datetime_utc, |
||
| 465 | reporting_end_datetime_utc) |
||
| 466 | tariff_timestamp_list = list() |
||
| 467 | tariff_value_list = list() |
||
| 468 | for k, v in energy_category_tariff_dict.items(): |
||
| 469 | # convert k from utc to local |
||
| 470 | k = k + timedelta(minutes=timezone_offset) |
||
| 471 | tariff_timestamp_list.append(k.isoformat()[0:19][0:19]) |
||
| 472 | tariff_value_list.append(v) |
||
| 473 | |||
| 474 | parameters_data['names'].append('TARIFF-' + energy_category_dict[energy_category_id]['name']) |
||
| 475 | parameters_data['timestamps'].append(tariff_timestamp_list) |
||
| 476 | parameters_data['values'].append(tariff_value_list) |
||
| 477 | |||
| 478 | ################################################################################################################ |
||
| 479 | # Step 10: query associated sensors and points data |
||
| 480 | ################################################################################################################ |
||
| 481 | for point in point_list: |
||
| 482 | point_values = [] |
||
| 483 | point_timestamps = [] |
||
| 484 | if point['object_type'] == 'ANALOG_VALUE': |
||
| 485 | query = (" SELECT utc_date_time, actual_value " |
||
| 486 | " FROM tbl_analog_value " |
||
| 487 | " WHERE point_id = %s " |
||
| 488 | " AND utc_date_time BETWEEN %s AND %s " |
||
| 489 | " ORDER BY utc_date_time ") |
||
| 490 | cursor_historical.execute(query, (point['id'], |
||
| 491 | reporting_start_datetime_utc, |
||
| 492 | reporting_end_datetime_utc)) |
||
| 493 | rows = cursor_historical.fetchall() |
||
| 494 | |||
| 495 | if rows is not None and len(rows) > 0: |
||
| 496 | for row in rows: |
||
| 497 | current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ |
||
| 498 | timedelta(minutes=timezone_offset) |
||
| 499 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
||
| 500 | point_timestamps.append(current_datetime) |
||
| 501 | point_values.append(row[1]) |
||
| 502 | |||
| 503 | elif point['object_type'] == 'ENERGY_VALUE': |
||
| 504 | query = (" SELECT utc_date_time, actual_value " |
||
| 505 | " FROM tbl_energy_value " |
||
| 506 | " WHERE point_id = %s " |
||
| 507 | " AND utc_date_time BETWEEN %s AND %s " |
||
| 508 | " ORDER BY utc_date_time ") |
||
| 509 | cursor_historical.execute(query, (point['id'], |
||
| 510 | reporting_start_datetime_utc, |
||
| 511 | reporting_end_datetime_utc)) |
||
| 512 | rows = cursor_historical.fetchall() |
||
| 513 | |||
| 514 | if rows is not None and len(rows) > 0: |
||
| 515 | for row in rows: |
||
| 516 | current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ |
||
| 517 | timedelta(minutes=timezone_offset) |
||
| 518 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
||
| 519 | point_timestamps.append(current_datetime) |
||
| 520 | point_values.append(row[1]) |
||
| 521 | elif point['object_type'] == 'DIGITAL_VALUE': |
||
| 522 | query = (" SELECT utc_date_time, actual_value " |
||
| 523 | " FROM tbl_digital_value " |
||
| 524 | " WHERE point_id = %s " |
||
| 525 | " AND utc_date_time BETWEEN %s AND %s ") |
||
| 526 | cursor_historical.execute(query, (point['id'], |
||
| 527 | reporting_start_datetime_utc, |
||
| 528 | reporting_end_datetime_utc)) |
||
| 529 | rows = cursor_historical.fetchall() |
||
| 530 | |||
| 531 | if rows is not None and len(rows) > 0: |
||
| 532 | for row in rows: |
||
| 533 | current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ |
||
| 534 | timedelta(minutes=timezone_offset) |
||
| 535 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
||
| 536 | point_timestamps.append(current_datetime) |
||
| 537 | point_values.append(row[1]) |
||
| 538 | |||
| 539 | parameters_data['names'].append(point['name'] + ' (' + point['units'] + ')') |
||
| 540 | parameters_data['timestamps'].append(point_timestamps) |
||
| 541 | parameters_data['values'].append(point_values) |
||
| 542 | |||
| 543 | ################################################################################################################ |
||
| 544 | # Step 11: construct the report |
||
| 545 | ################################################################################################################ |
||
| 546 | if cursor_system: |
||
| 547 | cursor_system.close() |
||
| 548 | if cnx_system: |
||
| 549 | cnx_system.disconnect() |
||
| 550 | |||
| 551 | if cursor_energy: |
||
| 552 | cursor_energy.close() |
||
| 553 | if cnx_energy: |
||
| 554 | cnx_energy.disconnect() |
||
| 555 | |||
| 556 | result = dict() |
||
| 557 | |||
| 558 | result['combined_equipment'] = dict() |
||
| 559 | result['combined_equipment']['name'] = combined_equipment['name'] |
||
| 560 | |||
| 561 | result['base_period_input'] = dict() |
||
| 562 | result['base_period_input']['names'] = list() |
||
| 563 | result['base_period_input']['units'] = list() |
||
| 564 | result['base_period_input']['timestamps'] = list() |
||
| 565 | result['base_period_input']['values'] = list() |
||
| 566 | result['base_period_input']['subtotals'] = list() |
||
| 567 | if energy_category_set_input is not None and len(energy_category_set_input) > 0: |
||
| 568 | for energy_category_id in energy_category_set_input: |
||
| 569 | result['base_period_input']['names'].append(energy_category_dict[energy_category_id]['name']) |
||
| 570 | result['base_period_input']['units'].append(energy_category_dict[energy_category_id]['unit_of_measure']) |
||
| 571 | result['base_period_input']['timestamps'].append(base_input[energy_category_id]['timestamps']) |
||
| 572 | result['base_period_input']['values'].append(base_input[energy_category_id]['values']) |
||
| 573 | result['base_period_input']['subtotals'].append(base_input[energy_category_id]['subtotal']) |
||
| 574 | |||
| 575 | result['base_period_output'] = dict() |
||
| 576 | result['base_period_output']['names'] = list() |
||
| 577 | result['base_period_output']['units'] = list() |
||
| 578 | result['base_period_output']['timestamps'] = list() |
||
| 579 | result['base_period_output']['values'] = list() |
||
| 580 | result['base_period_output']['subtotals'] = list() |
||
| 581 | |||
| 582 | if energy_category_set_output is not None and len(energy_category_set_output) > 0: |
||
| 583 | for energy_category_id in energy_category_set_output: |
||
| 584 | result['base_period_output']['names'].append(energy_category_dict[energy_category_id]['name']) |
||
| 585 | result['base_period_output']['units'].append( |
||
| 586 | energy_category_dict[energy_category_id]['unit_of_measure']) |
||
| 587 | result['base_period_output']['timestamps'].append(base_output[energy_category_id]['timestamps']) |
||
| 588 | result['base_period_output']['values'].append(base_output[energy_category_id]['values']) |
||
| 589 | result['base_period_output']['subtotals'].append(base_output[energy_category_id]['subtotal']) |
||
| 590 | |||
| 591 | result['base_period_efficiency'] = dict() |
||
| 592 | result['base_period_efficiency']['names'] = list() |
||
| 593 | result['base_period_efficiency']['units'] = list() |
||
| 594 | result['base_period_efficiency']['timestamps'] = list() |
||
| 595 | result['base_period_efficiency']['values'] = list() |
||
| 596 | result['base_period_efficiency']['cumulations'] = list() |
||
| 597 | |||
| 598 | if energy_category_set_output is not None and len(energy_category_set_output) > 0: |
||
| 599 | for energy_category_id_output in energy_category_set_output: |
||
| 600 | for energy_category_id_input in energy_category_set_input: |
||
| 601 | result['base_period_efficiency']['names'].append( |
||
| 602 | energy_category_dict[energy_category_id_output]['name'] + '/' + |
||
| 603 | energy_category_dict[energy_category_id_input]['name']) |
||
| 604 | result['base_period_efficiency']['units'].append( |
||
| 605 | energy_category_dict[energy_category_id_output]['unit_of_measure'] + '/' + |
||
| 606 | energy_category_dict[energy_category_id_input]['unit_of_measure']) |
||
| 607 | result['base_period_efficiency']['timestamps'].append( |
||
| 608 | base_output[energy_category_id_output]['timestamps']) |
||
| 609 | efficiency_values = list() |
||
| 610 | for i in range(len(base_output[energy_category_id_output]['timestamps'])): |
||
| 611 | efficiency_values.append((base_output[energy_category_id_output]['values'][i] / |
||
| 612 | base_input[energy_category_id_input]['values'][i]) |
||
| 613 | if base_input[energy_category_id_input]['values'][i] > Decimal(0.0) |
||
| 614 | else None) |
||
| 615 | result['base_period_efficiency']['values'].append(efficiency_values) |
||
| 616 | |||
| 617 | base_cumulation = (base_output[energy_category_id_output]['subtotal'] / |
||
| 618 | base_input[energy_category_id_input]['subtotal']) if \ |
||
| 619 | base_input[energy_category_id_input]['subtotal'] > Decimal(0.0) else None |
||
| 620 | result['base_period_efficiency']['cumulations'].append(base_cumulation) |
||
| 621 | |||
| 622 | result['reporting_period_input'] = dict() |
||
| 623 | result['reporting_period_input']['names'] = list() |
||
| 624 | result['reporting_period_input']['energy_category_ids'] = list() |
||
| 625 | result['reporting_period_input']['units'] = list() |
||
| 626 | result['reporting_period_input']['timestamps'] = list() |
||
| 627 | result['reporting_period_input']['values'] = list() |
||
| 628 | result['reporting_period_input']['subtotals'] = list() |
||
| 629 | result['reporting_period_input']['increment_rates'] = list() |
||
| 630 | |||
| 631 | if energy_category_set_input is not None and len(energy_category_set_input) > 0: |
||
| 632 | for energy_category_id in energy_category_set_input: |
||
| 633 | result['reporting_period_input']['names'].append(energy_category_dict[energy_category_id]['name']) |
||
| 634 | result['reporting_period_input']['energy_category_ids'].append(energy_category_id) |
||
| 635 | result['reporting_period_input']['units'].append( |
||
| 636 | energy_category_dict[energy_category_id]['unit_of_measure']) |
||
| 637 | result['reporting_period_input']['timestamps'].append( |
||
| 638 | reporting_input[energy_category_id]['timestamps']) |
||
| 639 | result['reporting_period_input']['values'].append( |
||
| 640 | reporting_input[energy_category_id]['values']) |
||
| 641 | result['reporting_period_input']['subtotals'].append( |
||
| 642 | reporting_input[energy_category_id]['subtotal']) |
||
| 643 | result['reporting_period_input']['increment_rates'].append( |
||
| 644 | (reporting_input[energy_category_id]['subtotal'] - |
||
| 645 | base_input[energy_category_id]['subtotal']) / |
||
| 646 | base_input[energy_category_id]['subtotal'] |
||
| 647 | if base_input[energy_category_id]['subtotal'] > 0.0 else None) |
||
| 648 | |||
| 649 | result['reporting_period_output'] = dict() |
||
| 650 | result['reporting_period_output']['names'] = list() |
||
| 651 | result['reporting_period_output']['energy_category_ids'] = list() |
||
| 652 | result['reporting_period_output']['units'] = list() |
||
| 653 | result['reporting_period_output']['timestamps'] = list() |
||
| 654 | result['reporting_period_output']['values'] = list() |
||
| 655 | result['reporting_period_output']['subtotals'] = list() |
||
| 656 | result['reporting_period_output']['increment_rates'] = list() |
||
| 657 | |||
| 658 | if energy_category_set_output is not None and len(energy_category_set_output) > 0: |
||
| 659 | for energy_category_id in energy_category_set_output: |
||
| 660 | result['reporting_period_output']['names'].append(energy_category_dict[energy_category_id]['name']) |
||
| 661 | result['reporting_period_output']['energy_category_ids'].append(energy_category_id) |
||
| 662 | result['reporting_period_output']['units'].append( |
||
| 663 | energy_category_dict[energy_category_id]['unit_of_measure']) |
||
| 664 | result['reporting_period_output']['timestamps'].append( |
||
| 665 | reporting_output[energy_category_id]['timestamps']) |
||
| 666 | result['reporting_period_output']['values'].append(reporting_output[energy_category_id]['values']) |
||
| 667 | result['reporting_period_output']['subtotals'].append(reporting_output[energy_category_id]['subtotal']) |
||
| 668 | result['reporting_period_output']['increment_rates'].append( |
||
| 669 | (reporting_output[energy_category_id]['subtotal'] - |
||
| 670 | base_output[energy_category_id]['subtotal']) / |
||
| 671 | base_output[energy_category_id]['subtotal'] |
||
| 672 | if base_output[energy_category_id]['subtotal'] > 0.0 else None) |
||
| 673 | |||
| 674 | result['reporting_period_efficiency'] = dict() |
||
| 675 | result['reporting_period_efficiency']['names'] = list() |
||
| 676 | result['reporting_period_efficiency']['units'] = list() |
||
| 677 | result['reporting_period_efficiency']['timestamps'] = list() |
||
| 678 | result['reporting_period_efficiency']['values'] = list() |
||
| 679 | result['reporting_period_efficiency']['cumulations'] = list() |
||
| 680 | result['reporting_period_efficiency']['increment_rates'] = list() |
||
| 681 | |||
| 682 | if energy_category_set_output is not None and len(energy_category_set_output) > 0: |
||
| 683 | for energy_category_id_output in energy_category_set_output: |
||
| 684 | for energy_category_id_input in energy_category_set_input: |
||
| 685 | result['reporting_period_efficiency']['names'].append( |
||
| 686 | energy_category_dict[energy_category_id_output]['name'] + '/' + |
||
| 687 | energy_category_dict[energy_category_id_input]['name']) |
||
| 688 | result['reporting_period_efficiency']['units'].append( |
||
| 689 | energy_category_dict[energy_category_id_output]['unit_of_measure'] + '/' + |
||
| 690 | energy_category_dict[energy_category_id_input]['unit_of_measure']) |
||
| 691 | result['reporting_period_efficiency']['timestamps'].append( |
||
| 692 | reporting_output[energy_category_id_output]['timestamps']) |
||
| 693 | efficiency_values = list() |
||
| 694 | for i in range(len(reporting_output[energy_category_id_output]['timestamps'])): |
||
| 695 | efficiency_values.append((reporting_output[energy_category_id_output]['values'][i] / |
||
| 696 | reporting_input[energy_category_id_input]['values'][i]) |
||
| 697 | if reporting_input[energy_category_id_input]['values'][i] > |
||
| 698 | Decimal(0.0) else None) |
||
| 699 | result['reporting_period_efficiency']['values'].append(efficiency_values) |
||
| 700 | |||
| 701 | base_cumulation = (base_output[energy_category_id_output]['subtotal'] / |
||
| 702 | base_input[energy_category_id_input]['subtotal']) if \ |
||
| 703 | base_input[energy_category_id_input]['subtotal'] > Decimal(0.0) else None |
||
| 704 | |||
| 705 | reporting_cumulation = (reporting_output[energy_category_id_output]['subtotal'] / |
||
| 706 | reporting_input[energy_category_id_input]['subtotal']) if \ |
||
| 707 | reporting_input[energy_category_id_input]['subtotal'] > Decimal(0.0) else None |
||
| 708 | |||
| 709 | result['reporting_period_efficiency']['cumulations'].append(reporting_cumulation) |
||
| 710 | result['reporting_period_efficiency']['increment_rates'].append( |
||
| 711 | ((reporting_cumulation - base_cumulation) / base_cumulation if (base_cumulation > Decimal(0.0)) |
||
| 712 | else None) |
||
| 713 | ) |
||
| 714 | |||
| 715 | result['parameters'] = { |
||
| 716 | "names": parameters_data['names'], |
||
| 717 | "timestamps": parameters_data['timestamps'], |
||
| 718 | "values": parameters_data['values'] |
||
| 719 | } |
||
| 720 | |||
| 721 | resp.body = json.dumps(result) |
||
| 722 |
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