myems /
myems-api
| Conditions | 117 |
| Total Lines | 609 |
| Code Lines | 454 |
| Lines | 41 |
| Ratio | 6.73 % |
| 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.spaceenergycategory.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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| 35 | @staticmethod |
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| 36 | def on_get(req, resp): |
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| 37 | print(req.params) |
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| 38 | space_id = req.params.get('spaceid') |
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| 39 | period_type = req.params.get('periodtype') |
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| 40 | base_start_datetime_local = req.params.get('baseperiodstartdatetime') |
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| 41 | base_end_datetime_local = req.params.get('baseperiodenddatetime') |
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| 42 | reporting_start_datetime_local = req.params.get('reportingperiodstartdatetime') |
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| 43 | reporting_end_datetime_local = req.params.get('reportingperiodenddatetime') |
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| 44 | |||
| 45 | ################################################################################################################ |
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| 46 | # Step 1: valid parameters |
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| 47 | ################################################################################################################ |
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| 48 | if space_id is None: |
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| 49 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_SPACE_ID') |
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| 50 | else: |
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| 51 | space_id = str.strip(space_id) |
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| 52 | if not space_id.isdigit() or int(space_id) <= 0: |
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| 53 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_SPACE_ID') |
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| 54 | |||
| 55 | if period_type is None: |
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| 56 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_PERIOD_TYPE') |
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| 57 | else: |
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| 58 | period_type = str.strip(period_type) |
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| 59 | if period_type not in ['hourly', 'daily', 'monthly', 'yearly']: |
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| 60 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_PERIOD_TYPE') |
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| 61 | |||
| 62 | timezone_offset = int(config.utc_offset[1:3]) * 60 + int(config.utc_offset[4:6]) |
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| 63 | if config.utc_offset[0] == '-': |
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| 64 | timezone_offset = -timezone_offset |
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| 65 | |||
| 66 | base_start_datetime_utc = None |
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| 67 | if base_start_datetime_local is not None and len(str.strip(base_start_datetime_local)) > 0: |
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| 68 | base_start_datetime_local = str.strip(base_start_datetime_local) |
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| 69 | try: |
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| 70 | base_start_datetime_utc = datetime.strptime(base_start_datetime_local, |
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| 71 | '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ |
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| 72 | timedelta(minutes=timezone_offset) |
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| 73 | except ValueError: |
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| 74 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 75 | description="API.INVALID_BASE_PERIOD_START_DATETIME") |
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| 76 | |||
| 77 | base_end_datetime_utc = None |
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| 78 | if base_end_datetime_local is not None and len(str.strip(base_end_datetime_local)) > 0: |
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| 79 | base_end_datetime_local = str.strip(base_end_datetime_local) |
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| 80 | try: |
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| 81 | base_end_datetime_utc = datetime.strptime(base_end_datetime_local, |
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| 82 | '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ |
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| 83 | timedelta(minutes=timezone_offset) |
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| 84 | except ValueError: |
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| 85 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 86 | description="API.INVALID_BASE_PERIOD_END_DATETIME") |
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| 87 | |||
| 88 | if base_start_datetime_utc is not None and base_end_datetime_utc is not None and \ |
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| 89 | base_start_datetime_utc >= base_end_datetime_utc: |
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| 90 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 91 | description='API.INVALID_BASE_PERIOD_END_DATETIME') |
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| 92 | |||
| 93 | if reporting_start_datetime_local is None: |
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| 94 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 95 | description="API.INVALID_REPORTING_PERIOD_START_DATETIME") |
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| 96 | else: |
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| 97 | reporting_start_datetime_local = str.strip(reporting_start_datetime_local) |
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| 98 | try: |
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| 99 | reporting_start_datetime_utc = datetime.strptime(reporting_start_datetime_local, |
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| 100 | '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ |
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| 101 | timedelta(minutes=timezone_offset) |
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| 102 | except ValueError: |
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| 103 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 104 | description="API.INVALID_REPORTING_PERIOD_START_DATETIME") |
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| 105 | |||
| 106 | if reporting_end_datetime_local is None: |
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| 107 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 108 | description="API.INVALID_REPORTING_PERIOD_END_DATETIME") |
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| 109 | else: |
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| 110 | reporting_end_datetime_local = str.strip(reporting_end_datetime_local) |
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| 111 | try: |
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| 112 | reporting_end_datetime_utc = datetime.strptime(reporting_end_datetime_local, |
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| 113 | '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ |
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| 114 | timedelta(minutes=timezone_offset) |
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| 115 | except ValueError: |
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| 116 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 117 | description="API.INVALID_REPORTING_PERIOD_END_DATETIME") |
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| 118 | |||
| 119 | if reporting_start_datetime_utc >= reporting_end_datetime_utc: |
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| 120 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 121 | description='API.INVALID_REPORTING_PERIOD_END_DATETIME') |
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| 122 | |||
| 123 | ################################################################################################################ |
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| 124 | # Step 2: query the space |
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| 125 | ################################################################################################################ |
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| 126 | cnx_system = mysql.connector.connect(**config.myems_system_db) |
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| 127 | cursor_system = cnx_system.cursor() |
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| 128 | |||
| 129 | cnx_energy = mysql.connector.connect(**config.myems_energy_db) |
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| 130 | cursor_energy = cnx_energy.cursor() |
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| 131 | |||
| 132 | cnx_historical = mysql.connector.connect(**config.myems_historical_db) |
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| 133 | cursor_historical = cnx_historical.cursor() |
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| 134 | |||
| 135 | cursor_system.execute(" SELECT id, name, area, cost_center_id " |
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| 136 | " FROM tbl_spaces " |
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| 137 | " WHERE id = %s ", (space_id,)) |
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| 138 | row_space = cursor_system.fetchone() |
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| 139 | if row_space is None: |
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| 140 | if cursor_system: |
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| 141 | cursor_system.close() |
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| 142 | if cnx_system: |
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| 143 | cnx_system.disconnect() |
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| 144 | |||
| 145 | if cursor_energy: |
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| 146 | cursor_energy.close() |
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| 147 | if cnx_energy: |
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| 148 | cnx_energy.disconnect() |
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| 149 | |||
| 150 | if cnx_historical: |
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| 151 | cnx_historical.close() |
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| 152 | if cursor_historical: |
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| 153 | cursor_historical.disconnect() |
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| 154 | raise falcon.HTTPError(falcon.HTTP_404, title='API.NOT_FOUND', description='API.SPACE_NOT_FOUND') |
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| 155 | |||
| 156 | space = dict() |
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| 157 | space['id'] = row_space[0] |
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| 158 | space['name'] = row_space[1] |
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| 159 | space['area'] = row_space[2] |
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| 160 | space['cost_center_id'] = row_space[3] |
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| 161 | |||
| 162 | ################################################################################################################ |
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| 163 | # Step 3: query energy categories |
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| 164 | ################################################################################################################ |
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| 165 | energy_category_set = set() |
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| 166 | # query energy categories in base period |
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| 167 | cursor_energy.execute(" SELECT DISTINCT(energy_category_id) " |
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| 168 | " FROM tbl_space_input_category_hourly " |
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| 169 | " WHERE space_id = %s " |
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| 170 | " AND start_datetime_utc >= %s " |
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| 171 | " AND start_datetime_utc < %s ", |
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| 172 | (space['id'], base_start_datetime_utc, base_end_datetime_utc)) |
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| 173 | rows_energy_categories = cursor_energy.fetchall() |
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| 174 | if rows_energy_categories is not None or len(rows_energy_categories) > 0: |
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| 175 | for row_energy_category in rows_energy_categories: |
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| 176 | energy_category_set.add(row_energy_category[0]) |
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| 177 | |||
| 178 | # query energy categories in reporting period |
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| 179 | cursor_energy.execute(" SELECT DISTINCT(energy_category_id) " |
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| 180 | " FROM tbl_space_input_category_hourly " |
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| 181 | " WHERE space_id = %s " |
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| 182 | " AND start_datetime_utc >= %s " |
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| 183 | " AND start_datetime_utc < %s ", |
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| 184 | (space['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) |
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| 185 | rows_energy_categories = cursor_energy.fetchall() |
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| 186 | if rows_energy_categories is not None or len(rows_energy_categories) > 0: |
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| 187 | for row_energy_category in rows_energy_categories: |
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| 188 | energy_category_set.add(row_energy_category[0]) |
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| 189 | |||
| 190 | # query all energy categories in base period and reporting period |
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| 191 | cursor_system.execute(" SELECT id, name, unit_of_measure, kgce, kgco2e " |
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| 192 | " FROM tbl_energy_categories " |
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| 193 | " ORDER BY id ", ) |
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| 194 | rows_energy_categories = cursor_system.fetchall() |
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| 195 | if rows_energy_categories is None or len(rows_energy_categories) == 0: |
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| 196 | if cursor_system: |
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| 197 | cursor_system.close() |
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| 198 | if cnx_system: |
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| 199 | cnx_system.disconnect() |
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| 200 | |||
| 201 | if cursor_energy: |
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| 202 | cursor_energy.close() |
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| 203 | if cnx_energy: |
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| 204 | cnx_energy.disconnect() |
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| 205 | |||
| 206 | if cnx_historical: |
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| 207 | cnx_historical.close() |
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| 208 | if cursor_historical: |
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| 209 | cursor_historical.disconnect() |
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| 210 | raise falcon.HTTPError(falcon.HTTP_404, |
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| 211 | title='API.NOT_FOUND', |
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| 212 | description='API.ENERGY_CATEGORY_NOT_FOUND') |
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| 213 | energy_category_dict = dict() |
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| 214 | for row_energy_category in rows_energy_categories: |
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| 215 | if row_energy_category[0] in energy_category_set: |
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| 216 | energy_category_dict[row_energy_category[0]] = {"name": row_energy_category[1], |
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| 217 | "unit_of_measure": row_energy_category[2], |
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| 218 | "kgce": row_energy_category[3], |
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| 219 | "kgco2e": row_energy_category[4]} |
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| 220 | |||
| 221 | ################################################################################################################ |
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| 222 | # Step 4: query associated sensors |
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| 223 | ################################################################################################################ |
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| 224 | point_list = list() |
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| 225 | cursor_system.execute(" SELECT po.id, po.name, po.units, po.object_type " |
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| 226 | " FROM tbl_spaces sp, tbl_sensors se, tbl_spaces_sensors spse, " |
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| 227 | " tbl_points po, tbl_sensors_points sepo " |
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| 228 | " WHERE sp.id = %s AND sp.id = spse.space_id AND spse.sensor_id = se.id " |
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| 229 | " AND se.id = sepo.sensor_id AND sepo.point_id = po.id " |
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| 230 | " ORDER BY po.id ", (space['id'], )) |
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| 231 | rows_points = cursor_system.fetchall() |
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| 232 | if rows_points is not None and len(rows_points) > 0: |
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| 233 | for row in rows_points: |
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| 234 | point_list.append({"id": row[0], "name": row[1], "units": row[2], "object_type": row[3]}) |
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| 235 | |||
| 236 | ################################################################################################################ |
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| 237 | # Step 5: query associated points |
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| 238 | ################################################################################################################ |
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| 239 | cursor_system.execute(" SELECT po.id, po.name, po.units, po.object_type " |
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| 240 | " FROM tbl_spaces sp, tbl_spaces_points sppo, tbl_points po " |
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| 241 | " WHERE sp.id = %s AND sp.id = sppo.space_id AND sppo.point_id = po.id " |
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| 242 | " ORDER BY po.id ", (space['id'], )) |
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| 243 | rows_points = cursor_system.fetchall() |
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| 244 | if rows_points is not None and len(rows_points) > 0: |
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| 245 | for row in rows_points: |
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| 246 | point_list.append({"id": row[0], "name": row[1], "units": row[2], "object_type": row[3]}) |
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| 247 | |||
| 248 | ################################################################################################################ |
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| 249 | # Step 6: query child spaces |
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| 250 | ################################################################################################################ |
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| 251 | child_space_list = list() |
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| 252 | cursor_system.execute(" SELECT id, name " |
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| 253 | " FROM tbl_spaces " |
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| 254 | " WHERE parent_space_id = %s " |
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| 255 | " ORDER BY id ", (space['id'], )) |
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| 256 | rows_child_spaces = cursor_system.fetchall() |
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| 257 | if rows_child_spaces is not None and len(rows_child_spaces) > 0: |
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| 258 | for row in rows_child_spaces: |
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| 259 | child_space_list.append({"id": row[0], "name": row[1]}) |
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| 260 | |||
| 261 | ################################################################################################################ |
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| 262 | # Step 7: query base period energy input |
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| 263 | ################################################################################################################ |
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| 264 | base = dict() |
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| 265 | if energy_category_set is not None and len(energy_category_set) > 0: |
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| 266 | for energy_category_id in energy_category_set: |
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| 267 | kgce = energy_category_dict[energy_category_id]['kgce'] |
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| 268 | kgco2e = energy_category_dict[energy_category_id]['kgco2e'] |
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| 269 | |||
| 270 | base[energy_category_id] = dict() |
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| 271 | base[energy_category_id]['timestamps'] = list() |
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| 272 | base[energy_category_id]['values'] = list() |
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| 273 | base[energy_category_id]['subtotal'] = Decimal(0.0) |
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| 274 | base[energy_category_id]['subtotal_in_kgce'] = Decimal(0.0) |
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| 275 | base[energy_category_id]['subtotal_in_kgco2e'] = Decimal(0.0) |
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| 276 | |||
| 277 | cursor_energy.execute(" SELECT start_datetime_utc, actual_value " |
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| 278 | " FROM tbl_space_input_category_hourly " |
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| 279 | " WHERE space_id = %s " |
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| 280 | " AND energy_category_id = %s " |
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| 281 | " AND start_datetime_utc >= %s " |
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| 282 | " AND start_datetime_utc < %s " |
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| 283 | " ORDER BY start_datetime_utc ", |
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| 284 | (space['id'], |
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| 285 | energy_category_id, |
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| 286 | base_start_datetime_utc, |
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| 287 | base_end_datetime_utc)) |
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| 288 | rows_space_hourly = cursor_energy.fetchall() |
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| 289 | |||
| 290 | rows_space_periodically = utilities.aggregate_hourly_data_by_period(rows_space_hourly, |
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| 291 | base_start_datetime_utc, |
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| 292 | base_end_datetime_utc, |
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| 293 | period_type) |
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| 294 | for row_space_periodically in rows_space_periodically: |
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| 295 | current_datetime_local = row_space_periodically[0].replace(tzinfo=timezone.utc) + \ |
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| 296 | timedelta(minutes=timezone_offset) |
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| 297 | if period_type == 'hourly': |
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| 298 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
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| 299 | elif period_type == 'daily': |
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| 300 | current_datetime = current_datetime_local.strftime('%Y-%m-%d') |
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| 301 | elif period_type == 'monthly': |
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| 302 | current_datetime = current_datetime_local.strftime('%Y-%m') |
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| 303 | elif period_type == 'yearly': |
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| 304 | current_datetime = current_datetime_local.strftime('%Y') |
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| 305 | |||
| 306 | actual_value = Decimal(0.0) if row_space_periodically[1] is None else row_space_periodically[1] |
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| 307 | base[energy_category_id]['timestamps'].append(current_datetime) |
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|
introduced
by
|
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| 308 | base[energy_category_id]['values'].append(actual_value) |
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| 309 | base[energy_category_id]['subtotal'] += actual_value |
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| 310 | base[energy_category_id]['subtotal_in_kgce'] += actual_value * kgce |
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| 311 | base[energy_category_id]['subtotal_in_kgco2e'] += actual_value * kgco2e |
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| 312 | |||
| 313 | ################################################################################################################ |
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| 314 | # Step 8: query reporting period energy input |
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| 315 | ################################################################################################################ |
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| 316 | reporting = dict() |
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| 317 | if energy_category_set is not None and len(energy_category_set) > 0: |
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| 318 | for energy_category_id in energy_category_set: |
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| 319 | kgce = energy_category_dict[energy_category_id]['kgce'] |
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| 320 | kgco2e = energy_category_dict[energy_category_id]['kgco2e'] |
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| 321 | |||
| 322 | reporting[energy_category_id] = dict() |
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| 323 | reporting[energy_category_id]['timestamps'] = list() |
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| 324 | reporting[energy_category_id]['values'] = list() |
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| 325 | reporting[energy_category_id]['subtotal'] = Decimal(0.0) |
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| 326 | reporting[energy_category_id]['subtotal_in_kgce'] = Decimal(0.0) |
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| 327 | reporting[energy_category_id]['subtotal_in_kgco2e'] = Decimal(0.0) |
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| 328 | reporting[energy_category_id]['toppeak'] = Decimal(0.0) |
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| 329 | reporting[energy_category_id]['onpeak'] = Decimal(0.0) |
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| 330 | reporting[energy_category_id]['midpeak'] = Decimal(0.0) |
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| 331 | reporting[energy_category_id]['offpeak'] = Decimal(0.0) |
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| 332 | |||
| 333 | cursor_energy.execute(" SELECT start_datetime_utc, actual_value " |
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| 334 | " FROM tbl_space_input_category_hourly " |
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| 335 | " WHERE space_id = %s " |
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| 336 | " AND energy_category_id = %s " |
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| 337 | " AND start_datetime_utc >= %s " |
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| 338 | " AND start_datetime_utc < %s " |
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| 339 | " ORDER BY start_datetime_utc ", |
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| 340 | (space['id'], |
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| 341 | energy_category_id, |
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| 342 | reporting_start_datetime_utc, |
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| 343 | reporting_end_datetime_utc)) |
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| 344 | rows_space_hourly = cursor_energy.fetchall() |
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| 345 | |||
| 346 | rows_space_periodically = utilities.aggregate_hourly_data_by_period(rows_space_hourly, |
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| 347 | reporting_start_datetime_utc, |
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| 348 | reporting_end_datetime_utc, |
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| 349 | period_type) |
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| 350 | for row_space_periodically in rows_space_periodically: |
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| 351 | current_datetime_local = row_space_periodically[0].replace(tzinfo=timezone.utc) + \ |
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| 352 | timedelta(minutes=timezone_offset) |
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| 353 | if period_type == 'hourly': |
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| 354 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
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| 355 | elif period_type == 'daily': |
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| 356 | current_datetime = current_datetime_local.strftime('%Y-%m-%d') |
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| 357 | elif period_type == 'monthly': |
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| 358 | current_datetime = current_datetime_local.strftime('%Y-%m') |
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| 359 | elif period_type == 'yearly': |
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| 360 | current_datetime = current_datetime_local.strftime('%Y') |
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| 361 | |||
| 362 | actual_value = Decimal(0.0) if row_space_periodically[1] is None else row_space_periodically[1] |
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| 363 | reporting[energy_category_id]['timestamps'].append(current_datetime) |
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| 364 | reporting[energy_category_id]['values'].append(actual_value) |
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| 365 | reporting[energy_category_id]['subtotal'] += actual_value |
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| 366 | reporting[energy_category_id]['subtotal_in_kgce'] += actual_value * kgce |
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| 367 | reporting[energy_category_id]['subtotal_in_kgco2e'] += actual_value * kgco2e |
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| 368 | |||
| 369 | energy_category_tariff_dict = utilities.get_energy_category_peak_types(space['cost_center_id'], |
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| 370 | energy_category_id, |
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| 371 | reporting_start_datetime_utc, |
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| 372 | reporting_end_datetime_utc) |
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| 373 | for row in rows_space_hourly: |
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| 374 | peak_type = energy_category_tariff_dict.get(row[0], None) |
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| 375 | if peak_type == 'toppeak': |
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| 376 | reporting[energy_category_id]['toppeak'] += row[1] |
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| 377 | elif peak_type == 'onpeak': |
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| 378 | reporting[energy_category_id]['onpeak'] += row[1] |
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| 379 | elif peak_type == 'midpeak': |
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| 380 | reporting[energy_category_id]['midpeak'] += row[1] |
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| 381 | elif peak_type == 'offpeak': |
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| 382 | reporting[energy_category_id]['offpeak'] += row[1] |
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| 383 | |||
| 384 | ################################################################################################################ |
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| 385 | # Step 9: query tariff data |
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| 386 | ################################################################################################################ |
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| 387 | parameters_data = dict() |
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| 388 | parameters_data['names'] = list() |
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| 389 | parameters_data['timestamps'] = list() |
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| 390 | parameters_data['values'] = list() |
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| 391 | if energy_category_set is not None and len(energy_category_set) > 0: |
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| 392 | for energy_category_id in energy_category_set: |
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| 393 | energy_category_tariff_dict = utilities.get_energy_category_tariffs(space['cost_center_id'], |
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| 394 | energy_category_id, |
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| 395 | reporting_start_datetime_utc, |
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| 396 | reporting_end_datetime_utc) |
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| 397 | tariff_timestamp_list = list() |
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| 398 | tariff_value_list = list() |
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| 399 | for k, v in energy_category_tariff_dict.items(): |
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| 400 | # convert k from utc to local |
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| 401 | k = k + timedelta(minutes=timezone_offset) |
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| 402 | tariff_timestamp_list.append(k.isoformat()[0:19][0:19]) |
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| 403 | tariff_value_list.append(v) |
||
| 404 | |||
| 405 | parameters_data['names'].append('TARIFF-' + energy_category_dict[energy_category_id]['name']) |
||
| 406 | parameters_data['timestamps'].append(tariff_timestamp_list) |
||
| 407 | parameters_data['values'].append(tariff_value_list) |
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| 408 | |||
| 409 | ################################################################################################################ |
||
| 410 | # Step 10: query associated sensors and points data |
||
| 411 | ################################################################################################################ |
||
| 412 | for point in point_list: |
||
| 413 | point_values = [] |
||
| 414 | point_timestamps = [] |
||
| 415 | if point['object_type'] == 'ANALOG_VALUE': |
||
| 416 | query = (" SELECT utc_date_time, actual_value " |
||
| 417 | " FROM tbl_analog_value " |
||
| 418 | " WHERE point_id = %s " |
||
| 419 | " AND utc_date_time BETWEEN %s AND %s " |
||
| 420 | " ORDER BY utc_date_time ") |
||
| 421 | cursor_historical.execute(query, (point['id'], |
||
| 422 | reporting_start_datetime_utc, |
||
| 423 | reporting_end_datetime_utc)) |
||
| 424 | rows = cursor_historical.fetchall() |
||
| 425 | |||
| 426 | if rows is not None and len(rows) > 0: |
||
| 427 | for row in rows: |
||
| 428 | current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ |
||
| 429 | timedelta(minutes=timezone_offset) |
||
| 430 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
||
| 431 | point_timestamps.append(current_datetime) |
||
| 432 | point_values.append(row[1]) |
||
| 433 | |||
| 434 | elif point['object_type'] == 'ENERGY_VALUE': |
||
| 435 | query = (" SELECT utc_date_time, actual_value " |
||
| 436 | " FROM tbl_energy_value " |
||
| 437 | " WHERE point_id = %s " |
||
| 438 | " AND utc_date_time BETWEEN %s AND %s " |
||
| 439 | " ORDER BY utc_date_time ") |
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| 440 | cursor_historical.execute(query, (point['id'], |
||
| 441 | reporting_start_datetime_utc, |
||
| 442 | reporting_end_datetime_utc)) |
||
| 443 | rows = cursor_historical.fetchall() |
||
| 444 | |||
| 445 | if rows is not None and len(rows) > 0: |
||
| 446 | for row in rows: |
||
| 447 | current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ |
||
| 448 | timedelta(minutes=timezone_offset) |
||
| 449 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
||
| 450 | point_timestamps.append(current_datetime) |
||
| 451 | point_values.append(row[1]) |
||
| 452 | elif point['object_type'] == 'DIGITAL_VALUE': |
||
| 453 | query = (" SELECT utc_date_time, actual_value " |
||
| 454 | " FROM tbl_digital_value " |
||
| 455 | " WHERE point_id = %s " |
||
| 456 | " AND utc_date_time BETWEEN %s AND %s ") |
||
| 457 | cursor_historical.execute(query, (point['id'], |
||
| 458 | reporting_start_datetime_utc, |
||
| 459 | reporting_end_datetime_utc)) |
||
| 460 | rows = cursor_historical.fetchall() |
||
| 461 | |||
| 462 | if rows is not None and len(rows) > 0: |
||
| 463 | for row in rows: |
||
| 464 | current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ |
||
| 465 | timedelta(minutes=timezone_offset) |
||
| 466 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
||
| 467 | point_timestamps.append(current_datetime) |
||
| 468 | point_values.append(row[1]) |
||
| 469 | |||
| 470 | parameters_data['names'].append(point['name'] + ' (' + point['units'] + ')') |
||
| 471 | parameters_data['timestamps'].append(point_timestamps) |
||
| 472 | parameters_data['values'].append(point_values) |
||
| 473 | |||
| 474 | ################################################################################################################ |
||
| 475 | # Step 11: query child spaces energy input |
||
| 476 | ################################################################################################################ |
||
| 477 | child_space_data = dict() |
||
| 478 | |||
| 479 | View Code Duplication | if energy_category_set is not None and len(energy_category_set) > 0: |
|
| 480 | for energy_category_id in energy_category_set: |
||
| 481 | child_space_data[energy_category_id] = dict() |
||
| 482 | child_space_data[energy_category_id]['child_space_names'] = list() |
||
| 483 | child_space_data[energy_category_id]['subtotals'] = list() |
||
| 484 | child_space_data[energy_category_id]['subtotals_in_kgce'] = list() |
||
| 485 | child_space_data[energy_category_id]['subtotals_in_kgco2e'] = list() |
||
| 486 | kgce = energy_category_dict[energy_category_id]['kgce'] |
||
| 487 | kgco2e = energy_category_dict[energy_category_id]['kgco2e'] |
||
| 488 | for child_space in child_space_list: |
||
| 489 | child_space_data[energy_category_id]['child_space_names'].append(child_space['name']) |
||
| 490 | |||
| 491 | cursor_energy.execute(" SELECT SUM(actual_value) " |
||
| 492 | " FROM tbl_space_input_category_hourly " |
||
| 493 | " WHERE space_id = %s " |
||
| 494 | " AND energy_category_id = %s " |
||
| 495 | " AND start_datetime_utc >= %s " |
||
| 496 | " AND start_datetime_utc < %s " |
||
| 497 | " ORDER BY start_datetime_utc ", |
||
| 498 | (child_space['id'], |
||
| 499 | energy_category_id, |
||
| 500 | reporting_start_datetime_utc, |
||
| 501 | reporting_end_datetime_utc)) |
||
| 502 | row_subtotal = cursor_energy.fetchone() |
||
| 503 | |||
| 504 | subtotal = Decimal(0.0) if (row_subtotal is None or row_subtotal[0] is None) else row_subtotal[0] |
||
| 505 | child_space_data[energy_category_id]['subtotals'].append(subtotal) |
||
| 506 | child_space_data[energy_category_id]['subtotals_in_kgce'].append(subtotal * kgce) |
||
| 507 | child_space_data[energy_category_id]['subtotals_in_kgco2e'].append(subtotal * kgco2e) |
||
| 508 | |||
| 509 | ################################################################################################################ |
||
| 510 | # Step 12: construct the report |
||
| 511 | ################################################################################################################ |
||
| 512 | if cursor_system: |
||
| 513 | cursor_system.close() |
||
| 514 | if cnx_system: |
||
| 515 | cnx_system.disconnect() |
||
| 516 | |||
| 517 | if cursor_energy: |
||
| 518 | cursor_energy.close() |
||
| 519 | if cnx_energy: |
||
| 520 | cnx_energy.disconnect() |
||
| 521 | |||
| 522 | result = dict() |
||
| 523 | |||
| 524 | result['space'] = dict() |
||
| 525 | result['space']['name'] = space['name'] |
||
| 526 | result['space']['area'] = space['area'] |
||
| 527 | |||
| 528 | result['base_period'] = dict() |
||
| 529 | result['base_period']['names'] = list() |
||
| 530 | result['base_period']['units'] = list() |
||
| 531 | result['base_period']['timestamps'] = list() |
||
| 532 | result['base_period']['values'] = list() |
||
| 533 | result['base_period']['subtotals'] = list() |
||
| 534 | result['base_period']['subtotals_in_kgce'] = list() |
||
| 535 | result['base_period']['subtotals_in_kgco2e'] = list() |
||
| 536 | result['base_period']['total_in_kgce'] = Decimal(0.0) |
||
| 537 | result['base_period']['total_in_kgco2e'] = Decimal(0.0) |
||
| 538 | if energy_category_set is not None and len(energy_category_set) > 0: |
||
| 539 | for energy_category_id in energy_category_set: |
||
| 540 | result['base_period']['names'].append(energy_category_dict[energy_category_id]['name']) |
||
| 541 | result['base_period']['units'].append(energy_category_dict[energy_category_id]['unit_of_measure']) |
||
| 542 | result['base_period']['timestamps'].append(base[energy_category_id]['timestamps']) |
||
| 543 | result['base_period']['values'].append(base[energy_category_id]['values']) |
||
| 544 | result['base_period']['subtotals'].append(base[energy_category_id]['subtotal']) |
||
| 545 | result['base_period']['subtotals_in_kgce'].append(base[energy_category_id]['subtotal_in_kgce']) |
||
| 546 | result['base_period']['subtotals_in_kgco2e'].append(base[energy_category_id]['subtotal_in_kgco2e']) |
||
| 547 | result['base_period']['total_in_kgce'] += base[energy_category_id]['subtotal_in_kgce'] |
||
| 548 | result['base_period']['total_in_kgco2e'] += base[energy_category_id]['subtotal_in_kgco2e'] |
||
| 549 | |||
| 550 | result['reporting_period'] = dict() |
||
| 551 | result['reporting_period']['names'] = list() |
||
| 552 | result['reporting_period']['energy_category_ids'] = list() |
||
| 553 | result['reporting_period']['units'] = list() |
||
| 554 | result['reporting_period']['timestamps'] = list() |
||
| 555 | result['reporting_period']['values'] = list() |
||
| 556 | result['reporting_period']['subtotals'] = list() |
||
| 557 | result['reporting_period']['subtotals_in_kgce'] = list() |
||
| 558 | result['reporting_period']['subtotals_in_kgco2e'] = list() |
||
| 559 | result['reporting_period']['subtotals_per_unit_area'] = list() |
||
| 560 | result['reporting_period']['toppeaks'] = list() |
||
| 561 | result['reporting_period']['onpeaks'] = list() |
||
| 562 | result['reporting_period']['midpeaks'] = list() |
||
| 563 | result['reporting_period']['offpeaks'] = list() |
||
| 564 | result['reporting_period']['increment_rates'] = list() |
||
| 565 | result['reporting_period']['total_in_kgce'] = Decimal(0.0) |
||
| 566 | result['reporting_period']['total_in_kgco2e'] = Decimal(0.0) |
||
| 567 | result['reporting_period']['increment_rate_in_kgce'] = Decimal(0.0) |
||
| 568 | result['reporting_period']['increment_rate_in_kgco2e'] = Decimal(0.0) |
||
| 569 | |||
| 570 | if energy_category_set is not None and len(energy_category_set) > 0: |
||
| 571 | for energy_category_id in energy_category_set: |
||
| 572 | result['reporting_period']['names'].append(energy_category_dict[energy_category_id]['name']) |
||
| 573 | result['reporting_period']['energy_category_ids'].append(energy_category_id) |
||
| 574 | result['reporting_period']['units'].append(energy_category_dict[energy_category_id]['unit_of_measure']) |
||
| 575 | result['reporting_period']['timestamps'].append(reporting[energy_category_id]['timestamps']) |
||
| 576 | result['reporting_period']['values'].append(reporting[energy_category_id]['values']) |
||
| 577 | result['reporting_period']['subtotals'].append(reporting[energy_category_id]['subtotal']) |
||
| 578 | result['reporting_period']['subtotals_in_kgce'].append( |
||
| 579 | reporting[energy_category_id]['subtotal_in_kgce']) |
||
| 580 | result['reporting_period']['subtotals_in_kgco2e'].append( |
||
| 581 | reporting[energy_category_id]['subtotal_in_kgco2e']) |
||
| 582 | result['reporting_period']['subtotals_per_unit_area'].append( |
||
| 583 | reporting[energy_category_id]['subtotal'] / space['area'] if space['area'] > 0.0 else None) |
||
| 584 | result['reporting_period']['toppeaks'].append(reporting[energy_category_id]['toppeak']) |
||
| 585 | result['reporting_period']['onpeaks'].append(reporting[energy_category_id]['onpeak']) |
||
| 586 | result['reporting_period']['midpeaks'].append(reporting[energy_category_id]['midpeak']) |
||
| 587 | result['reporting_period']['offpeaks'].append(reporting[energy_category_id]['offpeak']) |
||
| 588 | result['reporting_period']['increment_rates'].append( |
||
| 589 | (reporting[energy_category_id]['subtotal'] - base[energy_category_id]['subtotal']) / |
||
| 590 | base[energy_category_id]['subtotal'] |
||
| 591 | if base[energy_category_id]['subtotal'] > 0.0 else None) |
||
| 592 | result['reporting_period']['total_in_kgce'] += reporting[energy_category_id]['subtotal_in_kgce'] |
||
| 593 | result['reporting_period']['total_in_kgco2e'] += reporting[energy_category_id]['subtotal_in_kgco2e'] |
||
| 594 | |||
| 595 | result['reporting_period']['total_in_kgco2e_per_unit_area'] = \ |
||
| 596 | result['reporting_period']['total_in_kgce'] / space['area'] if space['area'] > 0.0 else None |
||
| 597 | |||
| 598 | result['reporting_period']['increment_rate_in_kgce'] = \ |
||
| 599 | (result['reporting_period']['total_in_kgce'] - result['base_period']['total_in_kgce']) / \ |
||
| 600 | result['base_period']['total_in_kgce'] \ |
||
| 601 | if result['base_period']['total_in_kgce'] > Decimal(0.0) else None |
||
| 602 | |||
| 603 | result['reporting_period']['total_in_kgce_per_unit_area'] = \ |
||
| 604 | result['reporting_period']['total_in_kgco2e'] / space['area'] if space['area'] > 0.0 else None |
||
| 605 | |||
| 606 | result['reporting_period']['increment_rate_in_kgco2e'] = \ |
||
| 607 | (result['reporting_period']['total_in_kgco2e'] - result['base_period']['total_in_kgco2e']) / \ |
||
| 608 | result['base_period']['total_in_kgco2e'] \ |
||
| 609 | if result['base_period']['total_in_kgco2e'] > Decimal(0.0) else None |
||
| 610 | |||
| 611 | result['parameters'] = { |
||
| 612 | "names": parameters_data['names'], |
||
| 613 | "timestamps": parameters_data['timestamps'], |
||
| 614 | "values": parameters_data['values'] |
||
| 615 | } |
||
| 616 | |||
| 617 | result['child_space'] = dict() |
||
| 618 | result['child_space']['energy_category_names'] = list() # 1D array [energy category] |
||
| 619 | result['child_space']['units'] = list() # 1D array [energy category] |
||
| 620 | result['child_space']['child_space_names_array'] = list() # 2D array [energy category][child space] |
||
| 621 | result['child_space']['subtotals_array'] = list() # 2D array [energy category][child space] |
||
| 622 | result['child_space']['subtotals_in_kgce_array'] = list() # 2D array [energy category][child space] |
||
| 623 | result['child_space']['subtotals_in_kgco2e_array'] = list() # 2D array [energy category][child space] |
||
| 624 | View Code Duplication | if energy_category_set is not None and len(energy_category_set) > 0: |
|
| 625 | for energy_category_id in energy_category_set: |
||
| 626 | result['child_space']['energy_category_names'].append(energy_category_dict[energy_category_id]['name']) |
||
| 627 | result['child_space']['units'].append(energy_category_dict[energy_category_id]['unit_of_measure']) |
||
| 628 | result['child_space']['child_space_names_array'].append( |
||
| 629 | child_space_data[energy_category_id]['child_space_names']) |
||
| 630 | result['child_space']['subtotals_array'].append( |
||
| 631 | child_space_data[energy_category_id]['subtotals']) |
||
| 632 | result['child_space']['subtotals_in_kgce_array'].append( |
||
| 633 | child_space_data[energy_category_id]['subtotals_in_kgce']) |
||
| 634 | result['child_space']['subtotals_in_kgco2e_array'].append( |
||
| 635 | child_space_data[energy_category_id]['subtotals_in_kgco2e']) |
||
| 636 | # export result to Excel file and then encode the file to base64 string |
||
| 637 | result['excel_bytes_base64'] = excelexporters.spaceenergycategory.export(result, |
||
| 638 | space['name'], |
||
| 639 | reporting_start_datetime_local, |
||
| 640 | reporting_end_datetime_local, |
||
| 641 | period_type) |
||
| 642 | |||
| 643 | resp.body = json.dumps(result) |
||
| 644 |
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