myems /
myems-api
| Conditions | 144 |
| Total Lines | 692 |
| Code Lines | 513 |
| 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.spaceefficiency.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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| 34 | @staticmethod |
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| 35 | def on_get(req, resp): |
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| 36 | print(req.params) |
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| 37 | space_id = req.params.get('spaceid') |
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| 38 | period_type = req.params.get('periodtype') |
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| 39 | base_start_datetime_local = req.params.get('baseperiodstartdatetime') |
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| 40 | base_end_datetime_local = req.params.get('baseperiodenddatetime') |
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| 41 | reporting_start_datetime_local = req.params.get('reportingperiodstartdatetime') |
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| 42 | reporting_end_datetime_local = req.params.get('reportingperiodenddatetime') |
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| 43 | |||
| 44 | ################################################################################################################ |
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| 45 | # Step 1: valid parameters |
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| 46 | ################################################################################################################ |
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| 47 | if space_id is None: |
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| 48 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_SPACE_ID') |
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| 49 | else: |
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| 50 | space_id = str.strip(space_id) |
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| 51 | if not space_id.isdigit() or int(space_id) <= 0: |
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| 52 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_SPACE_ID') |
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| 53 | |||
| 54 | if period_type is None: |
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| 55 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_PERIOD_TYPE') |
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| 56 | else: |
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| 57 | period_type = str.strip(period_type) |
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| 58 | if period_type not in ['hourly', 'daily', 'monthly', 'yearly']: |
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| 59 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_PERIOD_TYPE') |
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| 60 | |||
| 61 | timezone_offset = int(config.utc_offset[1:3]) * 60 + int(config.utc_offset[4:6]) |
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| 62 | if config.utc_offset[0] == '-': |
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| 63 | timezone_offset = -timezone_offset |
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| 64 | |||
| 65 | base_start_datetime_utc = None |
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| 66 | if base_start_datetime_local is not None and len(str.strip(base_start_datetime_local)) > 0: |
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| 67 | base_start_datetime_local = str.strip(base_start_datetime_local) |
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| 68 | try: |
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| 69 | base_start_datetime_utc = datetime.strptime(base_start_datetime_local, |
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| 70 | '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ |
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| 71 | timedelta(minutes=timezone_offset) |
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| 72 | except ValueError: |
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| 73 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 74 | description="API.INVALID_BASE_PERIOD_START_DATETIME") |
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| 75 | |||
| 76 | base_end_datetime_utc = None |
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| 77 | if base_end_datetime_local is not None and len(str.strip(base_end_datetime_local)) > 0: |
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| 78 | base_end_datetime_local = str.strip(base_end_datetime_local) |
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| 79 | try: |
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| 80 | base_end_datetime_utc = datetime.strptime(base_end_datetime_local, |
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| 81 | '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ |
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| 82 | timedelta(minutes=timezone_offset) |
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| 83 | except ValueError: |
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| 84 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 85 | description="API.INVALID_BASE_PERIOD_END_DATETIME") |
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| 86 | |||
| 87 | if base_start_datetime_utc is not None and base_end_datetime_utc is not None and \ |
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| 88 | base_start_datetime_utc >= base_end_datetime_utc: |
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| 89 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 90 | description='API.INVALID_BASE_PERIOD_END_DATETIME') |
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| 91 | |||
| 92 | if reporting_start_datetime_local is None: |
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| 93 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 94 | description="API.INVALID_REPORTING_PERIOD_START_DATETIME") |
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| 95 | else: |
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| 96 | reporting_start_datetime_local = str.strip(reporting_start_datetime_local) |
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| 97 | try: |
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| 98 | reporting_start_datetime_utc = datetime.strptime(reporting_start_datetime_local, |
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| 99 | '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ |
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| 100 | timedelta(minutes=timezone_offset) |
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| 101 | except ValueError: |
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| 102 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 103 | description="API.INVALID_REPORTING_PERIOD_START_DATETIME") |
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| 104 | |||
| 105 | if reporting_end_datetime_local is None: |
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| 106 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 107 | description="API.INVALID_REPORTING_PERIOD_END_DATETIME") |
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| 108 | else: |
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| 109 | reporting_end_datetime_local = str.strip(reporting_end_datetime_local) |
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| 110 | try: |
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| 111 | reporting_end_datetime_utc = datetime.strptime(reporting_end_datetime_local, |
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| 112 | '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ |
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| 113 | timedelta(minutes=timezone_offset) |
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| 114 | except ValueError: |
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| 115 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 116 | description="API.INVALID_REPORTING_PERIOD_END_DATETIME") |
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| 117 | |||
| 118 | if reporting_start_datetime_utc >= reporting_end_datetime_utc: |
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| 119 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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| 120 | description='API.INVALID_REPORTING_PERIOD_END_DATETIME') |
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| 121 | |||
| 122 | ################################################################################################################ |
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| 123 | # Step 2: query the space |
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| 124 | ################################################################################################################ |
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| 125 | cnx_system = mysql.connector.connect(**config.myems_system_db) |
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| 126 | cursor_system = cnx_system.cursor() |
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| 127 | |||
| 128 | cnx_energy = mysql.connector.connect(**config.myems_energy_db) |
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| 129 | cursor_energy = cnx_energy.cursor() |
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| 130 | |||
| 131 | cnx_historical = mysql.connector.connect(**config.myems_historical_db) |
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| 132 | cursor_historical = cnx_historical.cursor() |
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| 133 | |||
| 134 | cursor_system.execute(" SELECT id, name, area, cost_center_id " |
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| 135 | " FROM tbl_spaces " |
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| 136 | " WHERE id = %s ", (space_id,)) |
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| 137 | row_space = cursor_system.fetchone() |
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| 138 | if row_space is None: |
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| 139 | if cursor_system: |
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| 140 | cursor_system.close() |
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| 141 | if cnx_system: |
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| 142 | cnx_system.disconnect() |
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| 143 | |||
| 144 | if cursor_energy: |
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| 145 | cursor_energy.close() |
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| 146 | if cnx_energy: |
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| 147 | cnx_energy.disconnect() |
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| 148 | |||
| 149 | if cnx_historical: |
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| 150 | cnx_historical.close() |
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| 151 | if cursor_historical: |
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| 152 | cursor_historical.disconnect() |
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| 153 | raise falcon.HTTPError(falcon.HTTP_404, title='API.NOT_FOUND', description='API.SPACE_NOT_FOUND') |
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| 154 | |||
| 155 | space = dict() |
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| 156 | space['id'] = row_space[0] |
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| 157 | space['name'] = row_space[1] |
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| 158 | space['area'] = row_space[2] |
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| 159 | space['cost_center_id'] = row_space[3] |
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| 160 | |||
| 161 | ################################################################################################################ |
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| 162 | # Step 3: query input energy categories and output energy categories |
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| 163 | ################################################################################################################ |
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| 164 | energy_category_set_input = set() |
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| 165 | energy_category_set_output = set() |
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| 166 | # query input 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_input.add(row_energy_category[0]) |
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| 177 | |||
| 178 | # query input 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_input.add(row_energy_category[0]) |
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| 189 | |||
| 190 | # query output energy categories in base period |
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| 191 | cursor_energy.execute(" SELECT DISTINCT(energy_category_id) " |
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| 192 | " FROM tbl_space_output_category_hourly " |
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| 193 | " WHERE space_id = %s " |
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| 194 | " AND start_datetime_utc >= %s " |
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| 195 | " AND start_datetime_utc < %s ", |
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| 196 | (space['id'], base_start_datetime_utc, base_end_datetime_utc)) |
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| 197 | rows_energy_categories = cursor_energy.fetchall() |
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| 198 | if rows_energy_categories is not None or len(rows_energy_categories) > 0: |
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| 199 | for row_energy_category in rows_energy_categories: |
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| 200 | energy_category_set_output.add(row_energy_category[0]) |
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| 201 | |||
| 202 | # query output energy categories in reporting period |
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| 203 | cursor_energy.execute(" SELECT DISTINCT(energy_category_id) " |
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| 204 | " FROM tbl_space_output_category_hourly " |
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| 205 | " WHERE space_id = %s " |
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| 206 | " AND start_datetime_utc >= %s " |
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| 207 | " AND start_datetime_utc < %s ", |
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| 208 | (space['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) |
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| 209 | rows_energy_categories = cursor_energy.fetchall() |
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| 210 | if rows_energy_categories is not None or len(rows_energy_categories) > 0: |
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| 211 | for row_energy_category in rows_energy_categories: |
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| 212 | energy_category_set_output.add(row_energy_category[0]) |
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| 213 | |||
| 214 | # query properties of all energy categories above |
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| 215 | cursor_system.execute(" SELECT id, name, unit_of_measure, kgce, kgco2e " |
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| 216 | " FROM tbl_energy_categories " |
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| 217 | " ORDER BY id ", ) |
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| 218 | rows_energy_categories = cursor_system.fetchall() |
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| 219 | if rows_energy_categories is None or len(rows_energy_categories) == 0: |
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| 220 | if cursor_system: |
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| 221 | cursor_system.close() |
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| 222 | if cnx_system: |
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| 223 | cnx_system.disconnect() |
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| 224 | |||
| 225 | if cursor_energy: |
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| 226 | cursor_energy.close() |
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| 227 | if cnx_energy: |
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| 228 | cnx_energy.disconnect() |
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| 229 | |||
| 230 | if cnx_historical: |
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| 231 | cnx_historical.close() |
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| 232 | if cursor_historical: |
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| 233 | cursor_historical.disconnect() |
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| 234 | raise falcon.HTTPError(falcon.HTTP_404, |
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| 235 | title='API.NOT_FOUND', |
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| 236 | description='API.ENERGY_CATEGORY_NOT_FOUND') |
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| 237 | energy_category_dict = dict() |
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| 238 | for row_energy_category in rows_energy_categories: |
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| 239 | if row_energy_category[0] in energy_category_set_input or \ |
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| 240 | row_energy_category[0] in energy_category_set_output: |
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| 241 | energy_category_dict[row_energy_category[0]] = {"name": row_energy_category[1], |
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| 242 | "unit_of_measure": row_energy_category[2], |
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| 243 | "kgce": row_energy_category[3], |
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| 244 | "kgco2e": row_energy_category[4]} |
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| 245 | |||
| 246 | ################################################################################################################ |
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| 247 | # Step 4: query associated sensors |
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| 248 | ################################################################################################################ |
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| 249 | point_list = list() |
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| 250 | cursor_system.execute(" SELECT po.id, po.name, po.units, po.object_type " |
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| 251 | " FROM tbl_spaces sp, tbl_sensors se, tbl_spaces_sensors spse, " |
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| 252 | " tbl_points po, tbl_sensors_points sepo " |
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| 253 | " WHERE sp.id = %s AND sp.id = spse.space_id AND spse.sensor_id = se.id " |
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| 254 | " AND se.id = sepo.sensor_id AND sepo.point_id = po.id " |
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| 255 | " ORDER BY po.id ", (space['id'], )) |
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| 256 | rows_points = cursor_system.fetchall() |
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| 257 | if rows_points is not None and len(rows_points) > 0: |
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| 258 | for row in rows_points: |
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| 259 | point_list.append({"id": row[0], "name": row[1], "units": row[2], "object_type": row[3]}) |
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| 260 | |||
| 261 | ################################################################################################################ |
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| 262 | # Step 5: query associated points |
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| 263 | ################################################################################################################ |
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| 264 | cursor_system.execute(" SELECT po.id, po.name, po.units, po.object_type " |
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| 265 | " FROM tbl_spaces sp, tbl_spaces_points sppo, tbl_points po " |
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| 266 | " WHERE sp.id = %s AND sp.id = sppo.space_id AND sppo.point_id = po.id " |
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| 267 | " ORDER BY po.id ", (space['id'], )) |
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| 268 | rows_points = cursor_system.fetchall() |
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| 269 | if rows_points is not None and len(rows_points) > 0: |
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| 270 | for row in rows_points: |
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| 271 | point_list.append({"id": row[0], "name": row[1], "units": row[2], "object_type": row[3]}) |
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| 272 | |||
| 273 | ################################################################################################################ |
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| 274 | # Step 6: query base period energy input |
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| 275 | ################################################################################################################ |
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| 276 | base_input = dict() |
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| 277 | if energy_category_set_input is not None and len(energy_category_set_input) > 0: |
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| 278 | for energy_category_id in energy_category_set_input: |
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| 279 | base_input[energy_category_id] = dict() |
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| 280 | base_input[energy_category_id]['timestamps'] = list() |
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| 281 | base_input[energy_category_id]['values'] = list() |
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| 282 | base_input[energy_category_id]['subtotal'] = Decimal(0.0) |
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| 283 | |||
| 284 | cursor_energy.execute(" SELECT start_datetime_utc, actual_value " |
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| 285 | " FROM tbl_space_input_category_hourly " |
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| 286 | " WHERE space_id = %s " |
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| 287 | " AND energy_category_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 | (space['id'], |
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| 292 | energy_category_id, |
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| 293 | base_start_datetime_utc, |
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| 294 | base_end_datetime_utc)) |
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| 295 | rows_space_hourly = cursor_energy.fetchall() |
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| 296 | |||
| 297 | rows_space_periodically = utilities.aggregate_hourly_data_by_period(rows_space_hourly, |
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| 298 | base_start_datetime_utc, |
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| 299 | base_end_datetime_utc, |
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| 300 | period_type) |
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| 301 | for row_space_periodically in rows_space_periodically: |
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| 302 | current_datetime_local = row_space_periodically[0].replace(tzinfo=timezone.utc) + \ |
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| 303 | timedelta(minutes=timezone_offset) |
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| 304 | if period_type == 'hourly': |
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| 305 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
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| 306 | elif period_type == 'daily': |
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| 307 | current_datetime = current_datetime_local.strftime('%Y-%m-%d') |
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| 308 | elif period_type == 'monthly': |
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| 309 | current_datetime = current_datetime_local.strftime('%Y-%m') |
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| 310 | elif period_type == 'yearly': |
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| 311 | current_datetime = current_datetime_local.strftime('%Y') |
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| 312 | |||
| 313 | actual_value = Decimal(0.0) if row_space_periodically[1] is None else row_space_periodically[1] |
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| 314 | base_input[energy_category_id]['timestamps'].append(current_datetime) |
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|
introduced
by
|
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| 315 | base_input[energy_category_id]['values'].append(actual_value) |
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| 316 | base_input[energy_category_id]['subtotal'] += actual_value |
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| 317 | |||
| 318 | ################################################################################################################ |
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| 319 | # Step 7: query base period energy output |
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| 320 | ################################################################################################################ |
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| 321 | base_output = dict() |
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| 322 | if energy_category_set_output is not None and len(energy_category_set_output) > 0: |
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| 323 | for energy_category_id in energy_category_set_output: |
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| 324 | base_output[energy_category_id] = dict() |
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| 325 | base_output[energy_category_id]['timestamps'] = list() |
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| 326 | base_output[energy_category_id]['values'] = list() |
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| 327 | base_output[energy_category_id]['subtotal'] = Decimal(0.0) |
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| 328 | |||
| 329 | cursor_energy.execute(" SELECT start_datetime_utc, actual_value " |
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| 330 | " FROM tbl_space_output_category_hourly " |
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| 331 | " WHERE space_id = %s " |
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| 332 | " AND energy_category_id = %s " |
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| 333 | " AND start_datetime_utc >= %s " |
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| 334 | " AND start_datetime_utc < %s " |
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| 335 | " ORDER BY start_datetime_utc ", |
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| 336 | (space['id'], |
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| 337 | energy_category_id, |
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| 338 | base_start_datetime_utc, |
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| 339 | base_end_datetime_utc)) |
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| 340 | rows_space_hourly = cursor_energy.fetchall() |
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| 341 | |||
| 342 | rows_space_periodically = utilities.aggregate_hourly_data_by_period(rows_space_hourly, |
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| 343 | base_start_datetime_utc, |
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| 344 | base_end_datetime_utc, |
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| 345 | period_type) |
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| 346 | for row_space_periodically in rows_space_periodically: |
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| 347 | current_datetime_local = row_space_periodically[0].replace(tzinfo=timezone.utc) + \ |
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| 348 | timedelta(minutes=timezone_offset) |
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| 349 | if period_type == 'hourly': |
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| 350 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
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| 351 | elif period_type == 'daily': |
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| 352 | current_datetime = current_datetime_local.strftime('%Y-%m-%d') |
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| 353 | elif period_type == 'monthly': |
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| 354 | current_datetime = current_datetime_local.strftime('%Y-%m') |
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| 355 | elif period_type == 'yearly': |
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| 356 | current_datetime = current_datetime_local.strftime('%Y') |
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| 357 | |||
| 358 | actual_value = Decimal(0.0) if row_space_periodically[1] is None else row_space_periodically[1] |
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| 359 | base_output[energy_category_id]['timestamps'].append(current_datetime) |
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| 360 | base_output[energy_category_id]['values'].append(actual_value) |
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| 361 | base_output[energy_category_id]['subtotal'] += actual_value |
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| 362 | ################################################################################################################ |
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| 363 | # Step 8: query reporting period energy input |
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| 364 | ################################################################################################################ |
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| 365 | reporting_input = dict() |
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| 366 | if energy_category_set_input is not None and len(energy_category_set_input) > 0: |
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| 367 | for energy_category_id in energy_category_set_input: |
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| 368 | |||
| 369 | reporting_input[energy_category_id] = dict() |
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| 370 | reporting_input[energy_category_id]['timestamps'] = list() |
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| 371 | reporting_input[energy_category_id]['values'] = list() |
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| 372 | reporting_input[energy_category_id]['subtotal'] = Decimal(0.0) |
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| 373 | |||
| 374 | cursor_energy.execute(" SELECT start_datetime_utc, actual_value " |
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| 375 | " FROM tbl_space_input_category_hourly " |
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| 376 | " WHERE space_id = %s " |
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| 377 | " AND energy_category_id = %s " |
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| 378 | " AND start_datetime_utc >= %s " |
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| 379 | " AND start_datetime_utc < %s " |
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| 380 | " ORDER BY start_datetime_utc ", |
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| 381 | (space['id'], |
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| 382 | energy_category_id, |
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| 383 | reporting_start_datetime_utc, |
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| 384 | reporting_end_datetime_utc)) |
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| 385 | rows_space_hourly = cursor_energy.fetchall() |
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| 386 | |||
| 387 | rows_space_periodically = utilities.aggregate_hourly_data_by_period(rows_space_hourly, |
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| 388 | reporting_start_datetime_utc, |
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| 389 | reporting_end_datetime_utc, |
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| 390 | period_type) |
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| 391 | for row_space_periodically in rows_space_periodically: |
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| 392 | current_datetime_local = row_space_periodically[0].replace(tzinfo=timezone.utc) + \ |
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| 393 | timedelta(minutes=timezone_offset) |
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| 394 | if period_type == 'hourly': |
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| 395 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
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| 396 | elif period_type == 'daily': |
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| 397 | current_datetime = current_datetime_local.strftime('%Y-%m-%d') |
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| 398 | elif period_type == 'monthly': |
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| 399 | current_datetime = current_datetime_local.strftime('%Y-%m') |
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| 400 | elif period_type == 'yearly': |
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| 401 | current_datetime = current_datetime_local.strftime('%Y') |
||
| 402 | |||
| 403 | actual_value = Decimal(0.0) if row_space_periodically[1] is None else row_space_periodically[1] |
||
| 404 | reporting_input[energy_category_id]['timestamps'].append(current_datetime) |
||
| 405 | reporting_input[energy_category_id]['values'].append(actual_value) |
||
| 406 | reporting_input[energy_category_id]['subtotal'] += actual_value |
||
| 407 | |||
| 408 | ################################################################################################################ |
||
| 409 | # Step 9: query reporting period energy output |
||
| 410 | ################################################################################################################ |
||
| 411 | reporting_output = dict() |
||
| 412 | if energy_category_set_output is not None and len(energy_category_set_output) > 0: |
||
| 413 | for energy_category_id in energy_category_set_output: |
||
| 414 | |||
| 415 | reporting_output[energy_category_id] = dict() |
||
| 416 | reporting_output[energy_category_id]['timestamps'] = list() |
||
| 417 | reporting_output[energy_category_id]['values'] = list() |
||
| 418 | reporting_output[energy_category_id]['subtotal'] = Decimal(0.0) |
||
| 419 | |||
| 420 | cursor_energy.execute(" SELECT start_datetime_utc, actual_value " |
||
| 421 | " FROM tbl_space_output_category_hourly " |
||
| 422 | " WHERE space_id = %s " |
||
| 423 | " AND energy_category_id = %s " |
||
| 424 | " AND start_datetime_utc >= %s " |
||
| 425 | " AND start_datetime_utc < %s " |
||
| 426 | " ORDER BY start_datetime_utc ", |
||
| 427 | (space['id'], |
||
| 428 | energy_category_id, |
||
| 429 | reporting_start_datetime_utc, |
||
| 430 | reporting_end_datetime_utc)) |
||
| 431 | rows_space_hourly = cursor_energy.fetchall() |
||
| 432 | |||
| 433 | rows_space_periodically = utilities.aggregate_hourly_data_by_period(rows_space_hourly, |
||
| 434 | reporting_start_datetime_utc, |
||
| 435 | reporting_end_datetime_utc, |
||
| 436 | period_type) |
||
| 437 | for row_space_periodically in rows_space_periodically: |
||
| 438 | current_datetime_local = row_space_periodically[0].replace(tzinfo=timezone.utc) + \ |
||
| 439 | timedelta(minutes=timezone_offset) |
||
| 440 | if period_type == 'hourly': |
||
| 441 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
||
| 442 | elif period_type == 'daily': |
||
| 443 | current_datetime = current_datetime_local.strftime('%Y-%m-%d') |
||
| 444 | elif period_type == 'monthly': |
||
| 445 | current_datetime = current_datetime_local.strftime('%Y-%m') |
||
| 446 | elif period_type == 'yearly': |
||
| 447 | current_datetime = current_datetime_local.strftime('%Y') |
||
| 448 | |||
| 449 | actual_value = Decimal(0.0) if row_space_periodically[1] is None else row_space_periodically[1] |
||
| 450 | reporting_output[energy_category_id]['timestamps'].append(current_datetime) |
||
| 451 | reporting_output[energy_category_id]['values'].append(actual_value) |
||
| 452 | reporting_output[energy_category_id]['subtotal'] += actual_value |
||
| 453 | |||
| 454 | ################################################################################################################ |
||
| 455 | # Step 10: query tariff data |
||
| 456 | ################################################################################################################ |
||
| 457 | parameters_data = dict() |
||
| 458 | parameters_data['names'] = list() |
||
| 459 | parameters_data['timestamps'] = list() |
||
| 460 | parameters_data['values'] = list() |
||
| 461 | if energy_category_set_input is not None and len(energy_category_set_input) > 0: |
||
| 462 | for energy_category_id in energy_category_set_input: |
||
| 463 | energy_category_tariff_dict = utilities.get_energy_category_tariffs(space['cost_center_id'], |
||
| 464 | energy_category_id, |
||
| 465 | reporting_start_datetime_utc, |
||
| 466 | reporting_end_datetime_utc) |
||
| 467 | tariff_timestamp_list = list() |
||
| 468 | tariff_value_list = list() |
||
| 469 | for k, v in energy_category_tariff_dict.items(): |
||
| 470 | # convert k from utc to local |
||
| 471 | k = k + timedelta(minutes=timezone_offset) |
||
| 472 | tariff_timestamp_list.append(k.isoformat()[0:19][0:19]) |
||
| 473 | tariff_value_list.append(v) |
||
| 474 | |||
| 475 | parameters_data['names'].append('TARIFF-' + energy_category_dict[energy_category_id]['name']) |
||
| 476 | parameters_data['timestamps'].append(tariff_timestamp_list) |
||
| 477 | parameters_data['values'].append(tariff_value_list) |
||
| 478 | |||
| 479 | ################################################################################################################ |
||
| 480 | # Step 11: query associated sensors and points data |
||
| 481 | ################################################################################################################ |
||
| 482 | for point in point_list: |
||
| 483 | point_values = [] |
||
| 484 | point_timestamps = [] |
||
| 485 | if point['object_type'] == 'ANALOG_VALUE': |
||
| 486 | query = (" SELECT utc_date_time, actual_value " |
||
| 487 | " FROM tbl_analog_value " |
||
| 488 | " WHERE point_id = %s " |
||
| 489 | " AND utc_date_time BETWEEN %s AND %s " |
||
| 490 | " ORDER BY utc_date_time ") |
||
| 491 | cursor_historical.execute(query, (point['id'], |
||
| 492 | reporting_start_datetime_utc, |
||
| 493 | reporting_end_datetime_utc)) |
||
| 494 | rows = cursor_historical.fetchall() |
||
| 495 | |||
| 496 | if rows is not None and len(rows) > 0: |
||
| 497 | for row in rows: |
||
| 498 | current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ |
||
| 499 | timedelta(minutes=timezone_offset) |
||
| 500 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
||
| 501 | point_timestamps.append(current_datetime) |
||
| 502 | point_values.append(row[1]) |
||
| 503 | |||
| 504 | elif point['object_type'] == 'ENERGY_VALUE': |
||
| 505 | query = (" SELECT utc_date_time, actual_value " |
||
| 506 | " FROM tbl_energy_value " |
||
| 507 | " WHERE point_id = %s " |
||
| 508 | " AND utc_date_time BETWEEN %s AND %s " |
||
| 509 | " ORDER BY utc_date_time ") |
||
| 510 | cursor_historical.execute(query, (point['id'], |
||
| 511 | reporting_start_datetime_utc, |
||
| 512 | reporting_end_datetime_utc)) |
||
| 513 | rows = cursor_historical.fetchall() |
||
| 514 | |||
| 515 | if rows is not None and len(rows) > 0: |
||
| 516 | for row in rows: |
||
| 517 | current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ |
||
| 518 | timedelta(minutes=timezone_offset) |
||
| 519 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
||
| 520 | point_timestamps.append(current_datetime) |
||
| 521 | point_values.append(row[1]) |
||
| 522 | elif point['object_type'] == 'DIGITAL_VALUE': |
||
| 523 | query = (" SELECT utc_date_time, actual_value " |
||
| 524 | " FROM tbl_digital_value " |
||
| 525 | " WHERE point_id = %s " |
||
| 526 | " AND utc_date_time BETWEEN %s AND %s ") |
||
| 527 | cursor_historical.execute(query, (point['id'], |
||
| 528 | reporting_start_datetime_utc, |
||
| 529 | reporting_end_datetime_utc)) |
||
| 530 | rows = cursor_historical.fetchall() |
||
| 531 | |||
| 532 | if rows is not None and len(rows) > 0: |
||
| 533 | for row in rows: |
||
| 534 | current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ |
||
| 535 | timedelta(minutes=timezone_offset) |
||
| 536 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
||
| 537 | point_timestamps.append(current_datetime) |
||
| 538 | point_values.append(row[1]) |
||
| 539 | |||
| 540 | parameters_data['names'].append(point['name'] + ' (' + point['units'] + ')') |
||
| 541 | parameters_data['timestamps'].append(point_timestamps) |
||
| 542 | parameters_data['values'].append(point_values) |
||
| 543 | |||
| 544 | ################################################################################################################ |
||
| 545 | # Step 12: construct the report |
||
| 546 | ################################################################################################################ |
||
| 547 | if cursor_system: |
||
| 548 | cursor_system.close() |
||
| 549 | if cnx_system: |
||
| 550 | cnx_system.disconnect() |
||
| 551 | |||
| 552 | if cursor_energy: |
||
| 553 | cursor_energy.close() |
||
| 554 | if cnx_energy: |
||
| 555 | cnx_energy.disconnect() |
||
| 556 | |||
| 557 | result = dict() |
||
| 558 | |||
| 559 | result['space'] = dict() |
||
| 560 | result['space']['name'] = space['name'] |
||
| 561 | result['space']['area'] = space['area'] |
||
| 562 | |||
| 563 | result['base_period_input'] = dict() |
||
| 564 | result['base_period_input']['names'] = list() |
||
| 565 | result['base_period_input']['units'] = list() |
||
| 566 | result['base_period_input']['timestamps'] = list() |
||
| 567 | result['base_period_input']['values'] = list() |
||
| 568 | result['base_period_input']['subtotals'] = list() |
||
| 569 | if energy_category_set_input is not None and len(energy_category_set_input) > 0: |
||
| 570 | for energy_category_id in energy_category_set_input: |
||
| 571 | result['base_period_input']['names'].append(energy_category_dict[energy_category_id]['name']) |
||
| 572 | result['base_period_input']['units'].append(energy_category_dict[energy_category_id]['unit_of_measure']) |
||
| 573 | result['base_period_input']['timestamps'].append(base_input[energy_category_id]['timestamps']) |
||
| 574 | result['base_period_input']['values'].append(base_input[energy_category_id]['values']) |
||
| 575 | result['base_period_input']['subtotals'].append(base_input[energy_category_id]['subtotal']) |
||
| 576 | |||
| 577 | result['base_period_output'] = dict() |
||
| 578 | result['base_period_output']['names'] = list() |
||
| 579 | result['base_period_output']['units'] = list() |
||
| 580 | result['base_period_output']['timestamps'] = list() |
||
| 581 | result['base_period_output']['values'] = list() |
||
| 582 | result['base_period_output']['subtotals'] = list() |
||
| 583 | |||
| 584 | if energy_category_set_output is not None and len(energy_category_set_output) > 0: |
||
| 585 | for energy_category_id in energy_category_set_output: |
||
| 586 | result['base_period_output']['names'].append(energy_category_dict[energy_category_id]['name']) |
||
| 587 | result['base_period_output']['units'].append( |
||
| 588 | energy_category_dict[energy_category_id]['unit_of_measure']) |
||
| 589 | result['base_period_output']['timestamps'].append(base_output[energy_category_id]['timestamps']) |
||
| 590 | result['base_period_output']['values'].append(base_output[energy_category_id]['values']) |
||
| 591 | result['base_period_output']['subtotals'].append(base_output[energy_category_id]['subtotal']) |
||
| 592 | |||
| 593 | result['base_period_efficiency'] = dict() |
||
| 594 | result['base_period_efficiency']['names'] = list() |
||
| 595 | result['base_period_efficiency']['units'] = list() |
||
| 596 | result['base_period_efficiency']['timestamps'] = list() |
||
| 597 | result['base_period_efficiency']['values'] = list() |
||
| 598 | result['base_period_efficiency']['cumulations'] = list() |
||
| 599 | |||
| 600 | if energy_category_set_output is not None and len(energy_category_set_output) > 0: |
||
| 601 | for energy_category_id_output in energy_category_set_output: |
||
| 602 | for energy_category_id_input in energy_category_set_input: |
||
| 603 | result['base_period_efficiency']['names'].append( |
||
| 604 | energy_category_dict[energy_category_id_output]['name'] + '/' + |
||
| 605 | energy_category_dict[energy_category_id_input]['name']) |
||
| 606 | result['base_period_efficiency']['units'].append( |
||
| 607 | energy_category_dict[energy_category_id_output]['unit_of_measure'] + '/' + |
||
| 608 | energy_category_dict[energy_category_id_input]['unit_of_measure']) |
||
| 609 | result['base_period_efficiency']['timestamps'].append( |
||
| 610 | base_output[energy_category_id_output]['timestamps']) |
||
| 611 | efficiency_values = list() |
||
| 612 | for i in range(len(base_output[energy_category_id_output]['timestamps'])): |
||
| 613 | efficiency_values.append((base_output[energy_category_id_output]['values'][i] / |
||
| 614 | base_input[energy_category_id_input]['values'][i]) |
||
| 615 | if base_input[energy_category_id_input]['values'][i] > Decimal(0.0) |
||
| 616 | else None) |
||
| 617 | result['base_period_efficiency']['values'].append(efficiency_values) |
||
| 618 | |||
| 619 | base_cumulation = (base_output[energy_category_id_output]['subtotal'] / |
||
| 620 | base_input[energy_category_id_input]['subtotal']) if \ |
||
| 621 | base_input[energy_category_id_input]['subtotal'] > Decimal(0.0) else None |
||
| 622 | result['base_period_efficiency']['cumulations'].append(base_cumulation) |
||
| 623 | |||
| 624 | result['reporting_period_input'] = dict() |
||
| 625 | result['reporting_period_input']['names'] = list() |
||
| 626 | result['reporting_period_input']['energy_category_ids'] = list() |
||
| 627 | result['reporting_period_input']['units'] = list() |
||
| 628 | result['reporting_period_input']['timestamps'] = list() |
||
| 629 | result['reporting_period_input']['values'] = list() |
||
| 630 | result['reporting_period_input']['subtotals'] = list() |
||
| 631 | result['reporting_period_input']['subtotals_per_unit_area'] = list() |
||
| 632 | result['reporting_period_input']['increment_rates'] = list() |
||
| 633 | |||
| 634 | if energy_category_set_input is not None and len(energy_category_set_input) > 0: |
||
| 635 | for energy_category_id in energy_category_set_input: |
||
| 636 | result['reporting_period_input']['names'].append(energy_category_dict[energy_category_id]['name']) |
||
| 637 | result['reporting_period_input']['energy_category_ids'].append(energy_category_id) |
||
| 638 | result['reporting_period_input']['units'].append( |
||
| 639 | energy_category_dict[energy_category_id]['unit_of_measure']) |
||
| 640 | result['reporting_period_input']['timestamps'].append( |
||
| 641 | reporting_input[energy_category_id]['timestamps']) |
||
| 642 | result['reporting_period_input']['values'].append( |
||
| 643 | reporting_input[energy_category_id]['values']) |
||
| 644 | result['reporting_period_input']['subtotals'].append( |
||
| 645 | reporting_input[energy_category_id]['subtotal']) |
||
| 646 | result['reporting_period_input']['increment_rates'].append( |
||
| 647 | (reporting_input[energy_category_id]['subtotal'] - |
||
| 648 | base_input[energy_category_id]['subtotal']) / |
||
| 649 | base_input[energy_category_id]['subtotal'] |
||
| 650 | if base_input[energy_category_id]['subtotal'] > 0.0 else None) |
||
| 651 | |||
| 652 | result['reporting_period_output'] = dict() |
||
| 653 | result['reporting_period_output']['names'] = list() |
||
| 654 | result['reporting_period_output']['energy_category_ids'] = list() |
||
| 655 | result['reporting_period_output']['units'] = list() |
||
| 656 | result['reporting_period_output']['timestamps'] = list() |
||
| 657 | result['reporting_period_output']['values'] = list() |
||
| 658 | result['reporting_period_output']['subtotals'] = list() |
||
| 659 | result['reporting_period_output']['subtotals_per_unit_area'] = list() |
||
| 660 | result['reporting_period_output']['increment_rates'] = list() |
||
| 661 | |||
| 662 | if energy_category_set_output is not None and len(energy_category_set_output) > 0: |
||
| 663 | for energy_category_id in energy_category_set_output: |
||
| 664 | result['reporting_period_output']['names'].append(energy_category_dict[energy_category_id]['name']) |
||
| 665 | result['reporting_period_output']['energy_category_ids'].append(energy_category_id) |
||
| 666 | result['reporting_period_output']['units'].append( |
||
| 667 | energy_category_dict[energy_category_id]['unit_of_measure']) |
||
| 668 | result['reporting_period_output']['timestamps'].append( |
||
| 669 | reporting_output[energy_category_id]['timestamps']) |
||
| 670 | result['reporting_period_output']['values'].append(reporting_output[energy_category_id]['values']) |
||
| 671 | result['reporting_period_output']['subtotals'].append(reporting_output[energy_category_id]['subtotal']) |
||
| 672 | result['reporting_period_output']['increment_rates'].append( |
||
| 673 | (reporting_output[energy_category_id]['subtotal'] - |
||
| 674 | base_output[energy_category_id]['subtotal']) / |
||
| 675 | base_output[energy_category_id]['subtotal'] |
||
| 676 | if base_output[energy_category_id]['subtotal'] > 0.0 else None) |
||
| 677 | |||
| 678 | result['reporting_period_efficiency'] = dict() |
||
| 679 | result['reporting_period_efficiency']['names'] = list() |
||
| 680 | result['reporting_period_efficiency']['units'] = list() |
||
| 681 | result['reporting_period_efficiency']['timestamps'] = list() |
||
| 682 | result['reporting_period_efficiency']['values'] = list() |
||
| 683 | result['reporting_period_efficiency']['cumulations'] = list() |
||
| 684 | result['reporting_period_efficiency']['increment_rates'] = list() |
||
| 685 | |||
| 686 | if energy_category_set_output is not None and len(energy_category_set_output) > 0: |
||
| 687 | for energy_category_id_output in energy_category_set_output: |
||
| 688 | for energy_category_id_input in energy_category_set_input: |
||
| 689 | result['reporting_period_efficiency']['names'].append( |
||
| 690 | energy_category_dict[energy_category_id_output]['name'] + '/' + |
||
| 691 | energy_category_dict[energy_category_id_input]['name']) |
||
| 692 | result['reporting_period_efficiency']['units'].append( |
||
| 693 | energy_category_dict[energy_category_id_output]['unit_of_measure'] + '/' + |
||
| 694 | energy_category_dict[energy_category_id_input]['unit_of_measure']) |
||
| 695 | result['reporting_period_efficiency']['timestamps'].append( |
||
| 696 | reporting_output[energy_category_id_output]['timestamps']) |
||
| 697 | efficiency_values = list() |
||
| 698 | for i in range(len(reporting_output[energy_category_id_output]['timestamps'])): |
||
| 699 | efficiency_values.append((reporting_output[energy_category_id_output]['values'][i] / |
||
| 700 | reporting_input[energy_category_id_input]['values'][i]) |
||
| 701 | if reporting_input[energy_category_id_input]['values'][i] > |
||
| 702 | Decimal(0.0) else None) |
||
| 703 | result['reporting_period_efficiency']['values'].append(efficiency_values) |
||
| 704 | |||
| 705 | base_cumulation = (base_output[energy_category_id_output]['subtotal'] / |
||
| 706 | base_input[energy_category_id_input]['subtotal']) if \ |
||
| 707 | base_input[energy_category_id_input]['subtotal'] > Decimal(0.0) else None |
||
| 708 | |||
| 709 | reporting_cumulation = (reporting_output[energy_category_id_output]['subtotal'] / |
||
| 710 | reporting_input[energy_category_id_input]['subtotal']) if \ |
||
| 711 | reporting_input[energy_category_id_input]['subtotal'] > Decimal(0.0) else None |
||
| 712 | |||
| 713 | result['reporting_period_efficiency']['cumulations'].append(reporting_cumulation) |
||
| 714 | result['reporting_period_efficiency']['increment_rates'].append( |
||
| 715 | ((reporting_cumulation - base_cumulation) / base_cumulation if (base_cumulation > Decimal(0.0)) |
||
| 716 | else None) |
||
| 717 | ) |
||
| 718 | |||
| 719 | result['parameters'] = { |
||
| 720 | "names": parameters_data['names'], |
||
| 721 | "timestamps": parameters_data['timestamps'], |
||
| 722 | "values": parameters_data['values'] |
||
| 723 | } |
||
| 724 | |||
| 725 | resp.body = json.dumps(result) |
||
| 726 |
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