MyEMS /
myems
| Conditions | 101 |
| Total Lines | 512 |
| Code Lines | 383 |
| Lines | 0 |
| Ratio | 0 % |
| 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 reports.virtualmetercomparison.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 | """ |
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| 64 | @staticmethod |
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| 65 | def on_get(req, resp): |
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| 66 | if 'API-KEY' not in req.headers or \ |
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| 67 | not isinstance(req.headers['API-KEY'], str) or \ |
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| 68 | len(str.strip(req.headers['API-KEY'])) == 0: |
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| 69 | access_control(req) |
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| 70 | else: |
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| 71 | api_key_control(req) |
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| 72 | print(req.params) |
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| 73 | # this procedure accepts virtual meter id or virtual meter uuid to identify a virtual meter |
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| 74 | virtual_meter_id1 = req.params.get('virtualmeterid1') |
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| 75 | virtual_meter_uuid1 = req.params.get('virtualmeteruuid1') |
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| 76 | virtual_meter_id2 = req.params.get('virtualmeterid2') |
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| 77 | virtual_meter_uuid2 = req.params.get('virtualmeteruuid2') |
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| 78 | period_type = req.params.get('periodtype') |
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| 79 | reporting_period_start_datetime_local = req.params.get('reportingperiodstartdatetime') |
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| 80 | reporting_period_end_datetime_local = req.params.get('reportingperiodenddatetime') |
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| 81 | language = req.params.get('language') |
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| 82 | quick_mode = req.params.get('quickmode') |
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| 83 | |||
| 84 | ################################################################################################################ |
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| 85 | # Step 1: valid parameters |
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| 86 | ################################################################################################################ |
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| 87 | if virtual_meter_id1 is None and virtual_meter_uuid1 is None: |
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| 88 | raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_VIRTUAL_METER_ID') |
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| 89 | |||
| 90 | if virtual_meter_id1 is not None: |
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| 91 | virtual_meter_id1 = str.strip(virtual_meter_id1) |
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| 92 | if not virtual_meter_id1.isdigit() or int(virtual_meter_id1) <= 0: |
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| 93 | raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 94 | description='API.INVALID_VIRTUAL_METER_ID') |
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| 95 | |||
| 96 | if virtual_meter_uuid1 is not None: |
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| 97 | regex = re.compile(r'^[a-f0-9]{8}-?[a-f0-9]{4}-?4[a-f0-9]{3}-?[89ab][a-f0-9]{3}-?[a-f0-9]{12}\Z', re.I) |
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| 98 | match = regex.match(str.strip(virtual_meter_uuid1)) |
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| 99 | if not bool(match): |
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| 100 | raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 101 | description='API.INVALID_VIRTUAL_METER_UUID') |
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| 102 | |||
| 103 | if virtual_meter_id2 is None and virtual_meter_uuid2 is None: |
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| 104 | raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 105 | description='API.INVALID_VIRTUAL_METER_ID') |
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| 106 | |||
| 107 | if virtual_meter_id2 is not None: |
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| 108 | virtual_meter_id2 = str.strip(virtual_meter_id2) |
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| 109 | if not virtual_meter_id2.isdigit() or int(virtual_meter_id2) <= 0: |
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| 110 | raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 111 | description='API.INVALID_VIRTUAL_METER_ID') |
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| 112 | |||
| 113 | if virtual_meter_uuid2 is not None: |
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| 114 | regex = re.compile(r'^[a-f0-9]{8}-?[a-f0-9]{4}-?4[a-f0-9]{3}-?[89ab][a-f0-9]{3}-?[a-f0-9]{12}\Z', re.I) |
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| 115 | match = regex.match(str.strip(virtual_meter_uuid2)) |
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| 116 | if not bool(match): |
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| 117 | raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 118 | description='API.INVALID_VIRTUAL_METER_UUID') |
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| 119 | |||
| 120 | if period_type is None: |
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| 121 | raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 122 | description='API.INVALID_PERIOD_TYPE') |
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| 123 | else: |
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| 124 | period_type = str.strip(period_type) |
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| 125 | if period_type not in ['hourly', 'daily', 'weekly', 'monthly', 'yearly']: |
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| 126 | raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 127 | description='API.INVALID_PERIOD_TYPE') |
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| 128 | |||
| 129 | timezone_offset = int(config.utc_offset[1:3]) * 60 + int(config.utc_offset[4:6]) |
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| 130 | if config.utc_offset[0] == '-': |
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| 131 | timezone_offset = -timezone_offset |
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| 132 | |||
| 133 | if reporting_period_start_datetime_local is None: |
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| 134 | raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 135 | description="API.INVALID_REPORTING_PERIOD_START_DATETIME") |
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| 136 | else: |
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| 137 | reporting_period_start_datetime_local = str.strip(reporting_period_start_datetime_local) |
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| 138 | try: |
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| 139 | reporting_start_datetime_utc = datetime.strptime(reporting_period_start_datetime_local, |
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| 140 | '%Y-%m-%dT%H:%M:%S') |
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| 141 | except ValueError: |
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| 142 | raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 143 | description="API.INVALID_REPORTING_PERIOD_START_DATETIME") |
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| 144 | reporting_start_datetime_utc = \ |
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| 145 | reporting_start_datetime_utc.replace(tzinfo=timezone.utc) - timedelta(minutes=timezone_offset) |
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| 146 | # nomalize the start datetime |
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| 147 | if config.minutes_to_count == 30 and reporting_start_datetime_utc.minute >= 30: |
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| 148 | reporting_start_datetime_utc = reporting_start_datetime_utc.replace(minute=30, second=0, microsecond=0) |
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| 149 | else: |
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| 150 | reporting_start_datetime_utc = reporting_start_datetime_utc.replace(minute=0, second=0, microsecond=0) |
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| 151 | |||
| 152 | if reporting_period_end_datetime_local is None: |
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| 153 | raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 154 | description="API.INVALID_REPORTING_PERIOD_END_DATETIME") |
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| 155 | else: |
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| 156 | reporting_period_end_datetime_local = str.strip(reporting_period_end_datetime_local) |
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| 157 | try: |
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| 158 | reporting_end_datetime_utc = datetime.strptime(reporting_period_end_datetime_local, |
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| 159 | '%Y-%m-%dT%H:%M:%S') |
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| 160 | except ValueError: |
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| 161 | raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 162 | description="API.INVALID_REPORTING_PERIOD_END_DATETIME") |
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| 163 | reporting_end_datetime_utc = reporting_end_datetime_utc.replace(tzinfo=timezone.utc) - \ |
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| 164 | timedelta(minutes=timezone_offset) |
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| 165 | |||
| 166 | if reporting_start_datetime_utc >= reporting_end_datetime_utc: |
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| 167 | raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 168 | description='API.INVALID_REPORTING_PERIOD_END_DATETIME') |
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| 169 | |||
| 170 | # if turn quick mode on, do not return parameters data and excel file |
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| 171 | is_quick_mode = False |
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| 172 | if quick_mode is not None and \ |
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| 173 | len(str.strip(quick_mode)) > 0 and \ |
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| 174 | str.lower(str.strip(quick_mode)) in ('true', 't', 'on', 'yes', 'y'): |
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| 175 | is_quick_mode = True |
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| 176 | |||
| 177 | ################################################################################################################ |
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| 178 | # Step 2: query the virtual meter and energy category |
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| 179 | ################################################################################################################ |
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| 180 | cnx_system = mysql.connector.connect(**config.myems_system_db) |
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| 181 | cursor_system = cnx_system.cursor() |
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| 182 | |||
| 183 | cnx_energy = mysql.connector.connect(** config.myems_energy_db) |
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| 184 | cursor_energy = cnx_energy.cursor() |
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| 185 | |||
| 186 | cnx_historical = mysql.connector.connect(**config.myems_historical_db) |
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| 187 | cursor_historical = cnx_historical.cursor() |
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| 188 | |||
| 189 | if virtual_meter_id1 is not None: |
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| 190 | cursor_system.execute(" SELECT vm.id, vm.name, vm.energy_category_id, ec.name, ec.unit_of_measure, vm.equation " |
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| 191 | " FROM tbl_virtual_meters vm, tbl_energy_categories ec " |
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| 192 | " WHERE vm.id = %s AND vm.energy_category_id = ec.id ", (virtual_meter_id1,)) |
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| 193 | row_virtual_meter1 = cursor_system.fetchone() |
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| 194 | elif virtual_meter_uuid1 is not None: |
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| 195 | cursor_system.execute(" SELECT vm.id, vm.name, vm.energy_category_id, ec.name, ec.unit_of_measure, vm.equation " |
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| 196 | " FROM tbl_virtual_meters vm, tbl_energy_categories ec " |
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| 197 | " WHERE vm.uuid = %s AND vm.energy_category_id = ec.id ", (virtual_meter_uuid1,)) |
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| 198 | row_virtual_meter1 = cursor_system.fetchone() |
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| 199 | |||
| 200 | if row_virtual_meter1 is None: |
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|
introduced
by
|
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| 201 | if cursor_system: |
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| 202 | cursor_system.close() |
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| 203 | if cnx_system: |
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| 204 | cnx_system.close() |
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| 205 | |||
| 206 | if cursor_energy: |
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| 207 | cursor_energy.close() |
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| 208 | if cnx_energy: |
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| 209 | cnx_energy.close() |
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| 210 | |||
| 211 | if cursor_historical: |
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| 212 | cursor_historical.close() |
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| 213 | if cnx_historical: |
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| 214 | cnx_historical.close() |
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| 215 | raise falcon.HTTPError(status=falcon.HTTP_404, title='API.NOT_FOUND', description='API.VIRTUAL_METER_NOT_FOUND') |
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| 216 | |||
| 217 | virtual_meter1 = dict() |
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| 218 | virtual_meter1['id'] = row_virtual_meter1[0] |
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| 219 | virtual_meter1['name'] = row_virtual_meter1[1] |
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| 220 | virtual_meter1['energy_category_id'] = row_virtual_meter1[2] |
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| 221 | virtual_meter1['energy_category_name'] = row_virtual_meter1[3] |
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| 222 | virtual_meter1['unit_of_measure'] = row_virtual_meter1[4] |
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| 223 | virtual_meter1['equation'] = row_virtual_meter1[5] |
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| 224 | |||
| 225 | if virtual_meter_id2 is not None: |
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| 226 | cursor_system.execute(" SELECT vm.id, vm.name, vm.energy_category_id, ec.name, ec.unit_of_measure, vm.equation " |
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| 227 | " FROM tbl_virtual_meters vm, tbl_energy_categories ec " |
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| 228 | " WHERE vm.id = %s AND vm.energy_category_id = ec.id ", (virtual_meter_id2,)) |
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| 229 | row_virtual_meter2 = cursor_system.fetchone() |
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| 230 | elif virtual_meter_uuid2 is not None: |
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| 231 | cursor_system.execute(" SELECT vm.id, vm.name, vm.energy_category_id, ec.name, ec.unit_of_measure, vm.equation " |
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| 232 | " FROM tbl_virtual_meters vm, tbl_energy_categories ec " |
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| 233 | " WHERE vm.uuid = %s AND vm.energy_category_id = ec.id ", (virtual_meter_uuid2,)) |
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| 234 | row_virtual_meter2 = cursor_system.fetchone() |
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| 235 | |||
| 236 | if row_virtual_meter2 is None: |
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| 237 | if cursor_system: |
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| 238 | cursor_system.close() |
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| 239 | if cnx_system: |
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| 240 | cnx_system.close() |
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| 241 | |||
| 242 | if cursor_energy: |
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| 243 | cursor_energy.close() |
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| 244 | if cnx_energy: |
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| 245 | cnx_energy.close() |
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| 246 | |||
| 247 | if cursor_historical: |
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| 248 | cursor_historical.close() |
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| 249 | if cnx_historical: |
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| 250 | cnx_historical.close() |
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| 251 | raise falcon.HTTPError(status=falcon.HTTP_404, title='API.NOT_FOUND', description='API.VIRTUAL_METER_NOT_FOUND') |
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| 252 | |||
| 253 | virtual_meter2 = dict() |
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| 254 | virtual_meter2['id'] = row_virtual_meter2[0] |
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| 255 | virtual_meter2['name'] = row_virtual_meter2[1] |
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| 256 | virtual_meter2['energy_category_id'] = row_virtual_meter2[2] |
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| 257 | virtual_meter2['energy_category_name'] = row_virtual_meter2[3] |
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| 258 | virtual_meter2['unit_of_measure'] = row_virtual_meter2[4] |
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| 259 | virtual_meter2['equation'] = row_virtual_meter2[5] |
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| 260 | |||
| 261 | ################################################################################################################ |
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| 262 | # Step 3: parse equation and get associated points |
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| 263 | ################################################################################################################ |
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| 264 | def parse_equation_and_get_points(equation, cursor_system): |
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| 265 | if not equation: |
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| 266 | return [] |
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| 267 | variables = re.findall(r'x\d+', equation) |
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| 268 | if not variables: |
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| 269 | return [] |
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| 270 | unique_vars = list(set(variables)) |
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| 271 | |||
| 272 | placeholders = ', '.join(['%s'] * len(unique_vars)) |
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| 273 | cursor_system.execute(f" SELECT p.id, p.name, p.units, p.object_type " |
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| 274 | f" FROM tbl_points p " |
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| 275 | f" WHERE p.name IN ({placeholders}) ", tuple(unique_vars)) |
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| 276 | rows = cursor_system.fetchall() |
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| 277 | return [{"id": row[0], "name": row[1], "units": row[2], "object_type": row[3]} for row in rows] |
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| 278 | |||
| 279 | point_list1 = parse_equation_and_get_points(virtual_meter1['equation'], cursor_system) |
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| 280 | point_list2 = parse_equation_and_get_points(virtual_meter2['equation'], cursor_system) |
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| 281 | |||
| 282 | ################################################################################################################ |
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| 283 | # Step 4: query reporting period energy consumption |
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| 284 | ################################################################################################################ |
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| 285 | query1 = (" SELECT start_datetime_utc, actual_value " |
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| 286 | " FROM tbl_virtual_meter_hourly " |
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| 287 | " WHERE virtual_meter_id = %s " |
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| 288 | " AND start_datetime_utc >= %s " |
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| 289 | " AND start_datetime_utc < %s " |
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| 290 | " ORDER BY start_datetime_utc ") |
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| 291 | cursor_energy.execute(query1, (virtual_meter1['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) |
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| 292 | rows_virtual_meter1_hourly = cursor_energy.fetchall() |
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| 293 | |||
| 294 | rows_virtual_meter1_periodically = utilities.aggregate_hourly_data_by_period(rows_virtual_meter1_hourly, |
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| 295 | reporting_start_datetime_utc, |
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| 296 | reporting_end_datetime_utc, |
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| 297 | period_type) |
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| 298 | reporting1 = dict() |
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| 299 | reporting1['timestamps'] = list() |
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| 300 | reporting1['values'] = list() |
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| 301 | reporting1['total_in_category'] = Decimal(0.0) |
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| 302 | |||
| 303 | for row_virtual_meter1_periodically in rows_virtual_meter1_periodically: |
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| 304 | current_datetime_local = row_virtual_meter1_periodically[0].replace(tzinfo=timezone.utc) + \ |
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| 305 | timedelta(minutes=timezone_offset) |
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| 306 | if period_type == 'hourly': |
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| 307 | current_datetime = current_datetime_local.isoformat()[0:19] |
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| 308 | elif period_type == 'daily': |
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| 309 | current_datetime = current_datetime_local.isoformat()[0:10] |
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| 310 | elif period_type == 'weekly': |
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| 311 | current_datetime = current_datetime_local.isoformat()[0:10] |
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| 312 | elif period_type == 'monthly': |
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| 313 | current_datetime = current_datetime_local.isoformat()[0:7] |
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| 314 | elif period_type == 'yearly': |
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| 315 | current_datetime = current_datetime_local.isoformat()[0:4] |
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| 316 | |||
| 317 | actual_value = Decimal(0.0) if row_virtual_meter1_periodically[1] is None else row_virtual_meter1_periodically[1] |
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| 318 | |||
| 319 | reporting1['timestamps'].append(current_datetime) |
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| 320 | reporting1['values'].append(actual_value) |
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| 321 | reporting1['total_in_category'] += actual_value |
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| 322 | |||
| 323 | query2 = (" SELECT start_datetime_utc, actual_value " |
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| 324 | " FROM tbl_virtual_meter_hourly " |
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| 325 | " WHERE virtual_meter_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 | cursor_energy.execute(query2, (virtual_meter2['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) |
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| 330 | rows_virtual_meter2_hourly = cursor_energy.fetchall() |
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| 331 | |||
| 332 | rows_virtual_meter2_periodically = utilities.aggregate_hourly_data_by_period(rows_virtual_meter2_hourly, |
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| 333 | reporting_start_datetime_utc, |
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| 334 | reporting_end_datetime_utc, |
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| 335 | period_type) |
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| 336 | reporting2 = dict() |
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| 337 | diff = dict() |
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| 338 | reporting2['timestamps'] = list() |
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| 339 | reporting2['values'] = list() |
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| 340 | reporting2['total_in_category'] = Decimal(0.0) |
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| 341 | diff['values'] = list() |
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| 342 | diff['total_in_category'] = Decimal(0.0) |
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| 343 | |||
| 344 | for row_virtual_meter2_periodically in rows_virtual_meter2_periodically: |
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| 345 | current_datetime_local = row_virtual_meter2_periodically[0].replace(tzinfo=timezone.utc) + \ |
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| 346 | timedelta(minutes=timezone_offset) |
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| 347 | if period_type == 'hourly': |
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| 348 | current_datetime = current_datetime_local.isoformat()[0:19] |
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| 349 | elif period_type == 'daily': |
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| 350 | current_datetime = current_datetime_local.isoformat()[0:10] |
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| 351 | elif period_type == 'weekly': |
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| 352 | current_datetime = current_datetime_local.isoformat()[0:10] |
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| 353 | elif period_type == 'monthly': |
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| 354 | current_datetime = current_datetime_local.isoformat()[0:7] |
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| 355 | elif period_type == 'yearly': |
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| 356 | current_datetime = current_datetime_local.isoformat()[0:4] |
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| 357 | |||
| 358 | actual_value = Decimal(0.0) if row_virtual_meter2_periodically[1] is None else row_virtual_meter2_periodically[1] |
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| 359 | |||
| 360 | reporting2['timestamps'].append(current_datetime) |
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| 361 | reporting2['values'].append(actual_value) |
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| 362 | reporting2['total_in_category'] += actual_value |
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| 363 | |||
| 364 | for virtual_meter1_value, virtual_meter2_value in zip(reporting1['values'], reporting2['values']): |
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| 365 | diff['values'].append(virtual_meter1_value - virtual_meter2_value) |
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| 366 | diff['total_in_category'] += virtual_meter1_value - virtual_meter2_value |
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| 367 | |||
| 368 | ################################################################################################################ |
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| 369 | # Step 5: query associated points data |
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| 370 | ################################################################################################################ |
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| 371 | parameters_data1 = dict() |
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| 372 | parameters_data1['names'] = list() |
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| 373 | parameters_data1['timestamps'] = list() |
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| 374 | parameters_data1['values'] = list() |
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| 375 | |||
| 376 | if not is_quick_mode: |
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| 377 | for point in point_list1: |
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| 378 | point_values = [] |
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| 379 | point_timestamps = [] |
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| 380 | if point['object_type'] == 'ENERGY_VALUE': |
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| 381 | query = (" SELECT utc_date_time, actual_value " |
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| 382 | " FROM tbl_energy_value " |
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| 383 | " WHERE point_id = %s " |
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| 384 | " AND utc_date_time BETWEEN %s AND %s " |
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| 385 | " ORDER BY utc_date_time ") |
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| 386 | cursor_historical.execute(query, (point['id'], |
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| 387 | reporting_start_datetime_utc, |
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| 388 | reporting_end_datetime_utc)) |
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| 389 | rows = cursor_historical.fetchall() |
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| 390 | |||
| 391 | if rows is not None and len(rows) > 0: |
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| 392 | for row in rows: |
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| 393 | current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ |
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| 394 | timedelta(minutes=timezone_offset) |
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| 395 | current_datetime = current_datetime_local.isoformat()[0:19] |
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| 396 | point_timestamps.append(current_datetime) |
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| 397 | point_values.append(row[1]) |
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| 398 | elif point['object_type'] == 'ANALOG_VALUE': |
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| 399 | query = (" SELECT utc_date_time, actual_value " |
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| 400 | " FROM tbl_analog_value " |
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| 401 | " WHERE point_id = %s " |
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| 402 | " AND utc_date_time BETWEEN %s AND %s " |
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| 403 | " ORDER BY utc_date_time ") |
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| 404 | cursor_historical.execute(query, (point['id'], |
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| 405 | reporting_start_datetime_utc, |
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| 406 | reporting_end_datetime_utc)) |
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| 407 | rows = cursor_historical.fetchall() |
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| 408 | |||
| 409 | if rows is not None and len(rows) > 0: |
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| 410 | for row in rows: |
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| 411 | current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ |
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| 412 | timedelta(minutes=timezone_offset) |
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| 413 | current_datetime = current_datetime_local.isoformat()[0:19] |
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| 414 | point_timestamps.append(current_datetime) |
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| 415 | point_values.append(row[1]) |
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| 416 | elif point['object_type'] == 'DIGITAL_VALUE': |
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| 417 | query = (" SELECT utc_date_time, actual_value " |
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| 418 | " FROM tbl_digital_value " |
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| 419 | " WHERE point_id = %s " |
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| 420 | " AND utc_date_time BETWEEN %s AND %s " |
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| 421 | " ORDER BY utc_date_time ") |
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| 422 | cursor_historical.execute(query, (point['id'], |
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| 423 | reporting_start_datetime_utc, |
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| 424 | reporting_end_datetime_utc)) |
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| 425 | rows = cursor_historical.fetchall() |
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| 426 | |||
| 427 | if rows is not None and len(rows) > 0: |
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| 428 | for row in rows: |
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| 429 | current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ |
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| 430 | timedelta(minutes=timezone_offset) |
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| 431 | current_datetime = current_datetime_local.isoformat()[0:19] |
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| 432 | point_timestamps.append(current_datetime) |
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| 433 | point_values.append(row[1]) |
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| 434 | |||
| 435 | parameters_data1['names'].append(point['name'] + ' (' + point['units'] + ')') |
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| 436 | parameters_data1['timestamps'].append(point_timestamps) |
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| 437 | parameters_data1['values'].append(point_values) |
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| 438 | |||
| 439 | parameters_data2 = dict() |
||
| 440 | parameters_data2['names'] = list() |
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| 441 | parameters_data2['timestamps'] = list() |
||
| 442 | parameters_data2['values'] = list() |
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| 443 | if not is_quick_mode: |
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| 444 | for point in point_list2: |
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| 445 | point_values = [] |
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| 446 | point_timestamps = [] |
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| 447 | if point['object_type'] == 'ENERGY_VALUE': |
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| 448 | query = (" SELECT utc_date_time, actual_value " |
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| 449 | " FROM tbl_energy_value " |
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| 450 | " WHERE point_id = %s " |
||
| 451 | " AND utc_date_time BETWEEN %s AND %s " |
||
| 452 | " ORDER BY utc_date_time ") |
||
| 453 | cursor_historical.execute(query, (point['id'], |
||
| 454 | reporting_start_datetime_utc, |
||
| 455 | reporting_end_datetime_utc)) |
||
| 456 | rows = cursor_historical.fetchall() |
||
| 457 | |||
| 458 | if rows is not None and len(rows) > 0: |
||
| 459 | for row in rows: |
||
| 460 | current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ |
||
| 461 | timedelta(minutes=timezone_offset) |
||
| 462 | current_datetime = current_datetime_local.isoformat()[0:19] |
||
| 463 | point_timestamps.append(current_datetime) |
||
| 464 | point_values.append(row[1]) |
||
| 465 | elif point['object_type'] == 'ANALOG_VALUE': |
||
| 466 | query = (" SELECT utc_date_time, actual_value " |
||
| 467 | " FROM tbl_analog_value " |
||
| 468 | " WHERE point_id = %s " |
||
| 469 | " AND utc_date_time BETWEEN %s AND %s " |
||
| 470 | " ORDER BY utc_date_time ") |
||
| 471 | cursor_historical.execute(query, (point['id'], |
||
| 472 | reporting_start_datetime_utc, |
||
| 473 | reporting_end_datetime_utc)) |
||
| 474 | rows = cursor_historical.fetchall() |
||
| 475 | |||
| 476 | if rows is not None and len(rows) > 0: |
||
| 477 | for row in rows: |
||
| 478 | current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ |
||
| 479 | timedelta(minutes=timezone_offset) |
||
| 480 | current_datetime = current_datetime_local.isoformat()[0:19] |
||
| 481 | point_timestamps.append(current_datetime) |
||
| 482 | point_values.append(row[1]) |
||
| 483 | elif point['object_type'] == 'DIGITAL_VALUE': |
||
| 484 | query = (" SELECT utc_date_time, actual_value " |
||
| 485 | " FROM tbl_digital_value " |
||
| 486 | " WHERE point_id = %s " |
||
| 487 | " AND utc_date_time BETWEEN %s AND %s " |
||
| 488 | " ORDER BY utc_date_time ") |
||
| 489 | cursor_historical.execute(query, (point['id'], |
||
| 490 | reporting_start_datetime_utc, |
||
| 491 | reporting_end_datetime_utc)) |
||
| 492 | rows = cursor_historical.fetchall() |
||
| 493 | |||
| 494 | if rows is not None and len(rows) > 0: |
||
| 495 | for row in rows: |
||
| 496 | current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ |
||
| 497 | timedelta(minutes=timezone_offset) |
||
| 498 | current_datetime = current_datetime_local.isoformat()[0:19] |
||
| 499 | point_timestamps.append(current_datetime) |
||
| 500 | point_values.append(row[1]) |
||
| 501 | |||
| 502 | parameters_data2['names'].append(point['name'] + ' (' + point['units'] + ')') |
||
| 503 | parameters_data2['timestamps'].append(point_timestamps) |
||
| 504 | parameters_data2['values'].append(point_values) |
||
| 505 | |||
| 506 | ################################################################################################################ |
||
| 507 | # Step 6: construct the report |
||
| 508 | ################################################################################################################ |
||
| 509 | if cursor_system: |
||
| 510 | cursor_system.close() |
||
| 511 | if cnx_system: |
||
| 512 | cnx_system.close() |
||
| 513 | |||
| 514 | if cursor_energy: |
||
| 515 | cursor_energy.close() |
||
| 516 | if cnx_energy: |
||
| 517 | cnx_energy.close() |
||
| 518 | |||
| 519 | if cursor_historical: |
||
| 520 | cursor_historical.close() |
||
| 521 | if cnx_historical: |
||
| 522 | cnx_historical.close() |
||
| 523 | |||
| 524 | result = { |
||
| 525 | "virtualmeter1": { |
||
| 526 | "name": virtual_meter1['name'], |
||
| 527 | "energy_category_id": virtual_meter1['energy_category_id'], |
||
| 528 | "energy_category_name": virtual_meter1['energy_category_name'], |
||
| 529 | "unit_of_measure": virtual_meter1['unit_of_measure'], |
||
| 530 | "equation": virtual_meter1['equation'] # 新增：返回方程式 |
||
| 531 | }, |
||
| 532 | "reporting_period1": { |
||
| 533 | "total_in_category": reporting1['total_in_category'], |
||
| 534 | "timestamps": reporting1['timestamps'], |
||
| 535 | "values": reporting1['values'], |
||
| 536 | }, |
||
| 537 | "parameters1": { |
||
| 538 | "names": parameters_data1['names'], |
||
| 539 | "timestamps": parameters_data1['timestamps'], |
||
| 540 | "values": parameters_data1['values'] |
||
| 541 | }, |
||
| 542 | "virtualmeter2": { |
||
| 543 | "name": virtual_meter2['name'], |
||
| 544 | "energy_category_id": virtual_meter2['energy_category_id'], |
||
| 545 | "energy_category_name": virtual_meter2['energy_category_name'], |
||
| 546 | "unit_of_measure": virtual_meter2['unit_of_measure'], |
||
| 547 | "equation": virtual_meter2['equation'] |
||
| 548 | }, |
||
| 549 | "reporting_period2": { |
||
| 550 | "total_in_category": reporting2['total_in_category'], |
||
| 551 | "timestamps": reporting2['timestamps'], |
||
| 552 | "values": reporting2['values'], |
||
| 553 | }, |
||
| 554 | "parameters2": { |
||
| 555 | "names": parameters_data2['names'], |
||
| 556 | "timestamps": parameters_data2['timestamps'], |
||
| 557 | "values": parameters_data2['values'] |
||
| 558 | }, |
||
| 559 | "diff": { |
||
| 560 | "values": diff['values'], |
||
| 561 | "total_in_category": diff['total_in_category'], |
||
| 562 | } |
||
| 563 | } |
||
| 564 | # export result to Excel file and then encode the file to base64 string |
||
| 565 | if not is_quick_mode: |
||
| 566 | result['excel_bytes_base64'] = \ |
||
| 567 | excelexporters.virtualmetercomparison.export(result, |
||
| 568 | virtual_meter1['name'], |
||
| 569 | virtual_meter2['name'], |
||
| 570 | reporting_period_start_datetime_local, |
||
| 571 | reporting_period_end_datetime_local, |
||
| 572 | period_type, |
||
| 573 | language) |
||
| 574 | |||
| 575 | resp.text = json.dumps(result) |
||
| 576 |
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