MyEMS /
myems
| Conditions | 137 |
| Total Lines | 676 |
| Code Lines | 518 |
| Lines | 72 |
| Ratio | 10.65 % |
| 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.combinedequipmentstatistics.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 re |
||
| 37 | @staticmethod |
||
| 38 | def on_get(req, resp): |
||
| 39 | if 'API-KEY' not in req.headers or \ |
||
| 40 | not isinstance(req.headers['API-KEY'], str) or \ |
||
| 41 | len(str.strip(req.headers['API-KEY'])) == 0: |
||
| 42 | access_control(req) |
||
| 43 | else: |
||
| 44 | api_key_control(req) |
||
| 45 | print(req.params) |
||
| 46 | combined_equipment_id = req.params.get('combinedequipmentid') |
||
| 47 | combined_equipment_uuid = req.params.get('combinedequipmentuuid') |
||
| 48 | period_type = req.params.get('periodtype') |
||
| 49 | base_period_start_datetime_local = req.params.get('baseperiodstartdatetime') |
||
| 50 | base_period_end_datetime_local = req.params.get('baseperiodenddatetime') |
||
| 51 | reporting_period_start_datetime_local = req.params.get('reportingperiodstartdatetime') |
||
| 52 | reporting_period_end_datetime_local = req.params.get('reportingperiodenddatetime') |
||
| 53 | language = req.params.get('language') |
||
| 54 | quick_mode = req.params.get('quickmode') |
||
| 55 | |||
| 56 | ################################################################################################################ |
||
| 57 | # Step 1: valid parameters |
||
| 58 | ################################################################################################################ |
||
| 59 | if combined_equipment_id is None and combined_equipment_uuid is None: |
||
| 60 | raise falcon.HTTPError(status=falcon.HTTP_400, |
||
| 61 | title='API.BAD_REQUEST', |
||
| 62 | description='API.INVALID_COMBINED_EQUIPMENT_ID') |
||
| 63 | |||
| 64 | if combined_equipment_id is not None: |
||
| 65 | combined_equipment_id = str.strip(combined_equipment_id) |
||
| 66 | if not combined_equipment_id.isdigit() or int(combined_equipment_id) <= 0: |
||
| 67 | raise falcon.HTTPError(status=falcon.HTTP_400, |
||
| 68 | title='API.BAD_REQUEST', |
||
| 69 | description='API.INVALID_COMBINED_EQUIPMENT_ID') |
||
| 70 | |||
| 71 | if combined_equipment_uuid is not None: |
||
| 72 | regex = re.compile(r'^[a-f0-9]{8}-?[a-f0-9]{4}-?4[a-f0-9]{3}-?[89ab][a-f0-9]{3}-?[a-f0-9]{12}\Z', re.I) |
||
| 73 | match = regex.match(str.strip(combined_equipment_uuid)) |
||
| 74 | if not bool(match): |
||
| 75 | raise falcon.HTTPError(status=falcon.HTTP_400, |
||
| 76 | title='API.BAD_REQUEST', |
||
| 77 | description='API.INVALID_COMBINED_EQUIPMENT_UUID') |
||
| 78 | |||
| 79 | if period_type is None: |
||
| 80 | raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
||
| 81 | description='API.INVALID_PERIOD_TYPE') |
||
| 82 | else: |
||
| 83 | period_type = str.strip(period_type) |
||
| 84 | if period_type not in ['hourly', 'daily', 'weekly', 'monthly', 'yearly']: |
||
| 85 | raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
||
| 86 | description='API.INVALID_PERIOD_TYPE') |
||
| 87 | |||
| 88 | timezone_offset = int(config.utc_offset[1:3]) * 60 + int(config.utc_offset[4:6]) |
||
| 89 | if config.utc_offset[0] == '-': |
||
| 90 | timezone_offset = -timezone_offset |
||
| 91 | |||
| 92 | base_start_datetime_utc = None |
||
| 93 | if base_period_start_datetime_local is not None and len(str.strip(base_period_start_datetime_local)) > 0: |
||
| 94 | base_period_start_datetime_local = str.strip(base_period_start_datetime_local) |
||
| 95 | try: |
||
| 96 | base_start_datetime_utc = datetime.strptime(base_period_start_datetime_local, '%Y-%m-%dT%H:%M:%S') |
||
| 97 | except ValueError: |
||
| 98 | raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
||
| 99 | description="API.INVALID_BASE_PERIOD_START_DATETIME") |
||
| 100 | base_start_datetime_utc = \ |
||
| 101 | base_start_datetime_utc.replace(tzinfo=timezone.utc) - timedelta(minutes=timezone_offset) |
||
| 102 | # nomalize the start datetime |
||
| 103 | if config.minutes_to_count == 30 and base_start_datetime_utc.minute >= 30: |
||
| 104 | base_start_datetime_utc = base_start_datetime_utc.replace(minute=30, second=0, microsecond=0) |
||
| 105 | else: |
||
| 106 | base_start_datetime_utc = base_start_datetime_utc.replace(minute=0, second=0, microsecond=0) |
||
| 107 | |||
| 108 | base_end_datetime_utc = None |
||
| 109 | if base_period_end_datetime_local is not None and len(str.strip(base_period_end_datetime_local)) > 0: |
||
| 110 | base_period_end_datetime_local = str.strip(base_period_end_datetime_local) |
||
| 111 | try: |
||
| 112 | base_end_datetime_utc = datetime.strptime(base_period_end_datetime_local, '%Y-%m-%dT%H:%M:%S') |
||
| 113 | except ValueError: |
||
| 114 | raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
||
| 115 | description="API.INVALID_BASE_PERIOD_END_DATETIME") |
||
| 116 | base_end_datetime_utc = \ |
||
| 117 | base_end_datetime_utc.replace(tzinfo=timezone.utc) - timedelta(minutes=timezone_offset) |
||
| 118 | |||
| 119 | if base_start_datetime_utc is not None and base_end_datetime_utc is not None and \ |
||
| 120 | base_start_datetime_utc >= base_end_datetime_utc: |
||
| 121 | raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
||
| 122 | description='API.INVALID_BASE_PERIOD_END_DATETIME') |
||
| 123 | |||
| 124 | if reporting_period_start_datetime_local is None: |
||
| 125 | raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
||
| 126 | description="API.INVALID_REPORTING_PERIOD_START_DATETIME") |
||
| 127 | else: |
||
| 128 | reporting_period_start_datetime_local = str.strip(reporting_period_start_datetime_local) |
||
| 129 | try: |
||
| 130 | reporting_start_datetime_utc = datetime.strptime(reporting_period_start_datetime_local, |
||
| 131 | '%Y-%m-%dT%H:%M:%S') |
||
| 132 | except ValueError: |
||
| 133 | raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
||
| 134 | description="API.INVALID_REPORTING_PERIOD_START_DATETIME") |
||
| 135 | reporting_start_datetime_utc = \ |
||
| 136 | reporting_start_datetime_utc.replace(tzinfo=timezone.utc) - timedelta(minutes=timezone_offset) |
||
| 137 | # nomalize the start datetime |
||
| 138 | if config.minutes_to_count == 30 and reporting_start_datetime_utc.minute >= 30: |
||
| 139 | reporting_start_datetime_utc = reporting_start_datetime_utc.replace(minute=30, second=0, microsecond=0) |
||
| 140 | else: |
||
| 141 | reporting_start_datetime_utc = reporting_start_datetime_utc.replace(minute=0, second=0, microsecond=0) |
||
| 142 | |||
| 143 | if reporting_period_end_datetime_local is None: |
||
| 144 | raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
||
| 145 | description="API.INVALID_REPORTING_PERIOD_END_DATETIME") |
||
| 146 | else: |
||
| 147 | reporting_period_end_datetime_local = str.strip(reporting_period_end_datetime_local) |
||
| 148 | try: |
||
| 149 | reporting_end_datetime_utc = datetime.strptime(reporting_period_end_datetime_local, |
||
| 150 | '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ |
||
| 151 | timedelta(minutes=timezone_offset) |
||
| 152 | except ValueError: |
||
| 153 | raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
||
| 154 | description="API.INVALID_REPORTING_PERIOD_END_DATETIME") |
||
| 155 | |||
| 156 | if reporting_start_datetime_utc >= reporting_end_datetime_utc: |
||
| 157 | raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
||
| 158 | description='API.INVALID_REPORTING_PERIOD_END_DATETIME') |
||
| 159 | |||
| 160 | # if turn quick mode on, do not return parameters data and excel file |
||
| 161 | is_quick_mode = False |
||
| 162 | if quick_mode is not None and \ |
||
| 163 | len(str.strip(quick_mode)) > 0 and \ |
||
| 164 | str.lower(str.strip(quick_mode)) in ('true', 't', 'on', 'yes', 'y'): |
||
| 165 | is_quick_mode = True |
||
| 166 | |||
| 167 | trans = utilities.get_translation(language) |
||
| 168 | trans.install() |
||
| 169 | _ = trans.gettext |
||
| 170 | |||
| 171 | ################################################################################################################ |
||
| 172 | # Step 2: query the combined equipment |
||
| 173 | ################################################################################################################ |
||
| 174 | cnx_system = mysql.connector.connect(**config.myems_system_db) |
||
| 175 | cursor_system = cnx_system.cursor() |
||
| 176 | |||
| 177 | cnx_energy = mysql.connector.connect(**config.myems_energy_db) |
||
| 178 | cursor_energy = cnx_energy.cursor() |
||
| 179 | |||
| 180 | cnx_historical = mysql.connector.connect(**config.myems_historical_db) |
||
| 181 | cursor_historical = cnx_historical.cursor() |
||
| 182 | |||
| 183 | if combined_equipment_id is not None: |
||
| 184 | cursor_system.execute(" SELECT id, name, cost_center_id " |
||
| 185 | " FROM tbl_combined_equipments " |
||
| 186 | " WHERE id = %s ", (combined_equipment_id,)) |
||
| 187 | row_combined_equipment = cursor_system.fetchone() |
||
| 188 | elif combined_equipment_uuid is not None: |
||
| 189 | cursor_system.execute(" SELECT id, name, cost_center_id " |
||
| 190 | " FROM tbl_combined_equipments " |
||
| 191 | " WHERE uuid = %s ", (combined_equipment_uuid,)) |
||
| 192 | row_combined_equipment = cursor_system.fetchone() |
||
| 193 | |||
| 194 | View Code Duplication | if row_combined_equipment is None: |
|
| 195 | if cursor_system: |
||
| 196 | cursor_system.close() |
||
| 197 | if cnx_system: |
||
| 198 | cnx_system.close() |
||
| 199 | |||
| 200 | if cursor_energy: |
||
| 201 | cursor_energy.close() |
||
| 202 | if cnx_energy: |
||
| 203 | cnx_energy.close() |
||
| 204 | |||
| 205 | if cursor_historical: |
||
| 206 | cursor_historical.close() |
||
| 207 | if cnx_historical: |
||
| 208 | cnx_historical.close() |
||
| 209 | raise falcon.HTTPError(status=falcon.HTTP_404, |
||
| 210 | title='API.NOT_FOUND', |
||
| 211 | description='API.COMBINED_EQUIPMENT_NOT_FOUND') |
||
| 212 | |||
| 213 | combined_equipment = dict() |
||
| 214 | combined_equipment['id'] = row_combined_equipment[0] |
||
| 215 | combined_equipment['name'] = row_combined_equipment[1] |
||
| 216 | combined_equipment['cost_center_id'] = row_combined_equipment[2] |
||
| 217 | |||
| 218 | ################################################################################################################ |
||
| 219 | # Step 3: query energy categories |
||
| 220 | ################################################################################################################ |
||
| 221 | energy_category_set = set() |
||
| 222 | # query energy categories in base period |
||
| 223 | cursor_energy.execute(" SELECT DISTINCT(energy_category_id) " |
||
| 224 | " FROM tbl_combined_equipment_input_category_hourly " |
||
| 225 | " WHERE combined_equipment_id = %s " |
||
| 226 | " AND start_datetime_utc >= %s " |
||
| 227 | " AND start_datetime_utc < %s ", |
||
| 228 | (combined_equipment['id'], base_start_datetime_utc, base_end_datetime_utc)) |
||
| 229 | rows_energy_categories = cursor_energy.fetchall() |
||
| 230 | if rows_energy_categories is not None and len(rows_energy_categories) > 0: |
||
| 231 | for row_energy_category in rows_energy_categories: |
||
| 232 | energy_category_set.add(row_energy_category[0]) |
||
| 233 | |||
| 234 | # query energy categories in reporting period |
||
| 235 | cursor_energy.execute(" SELECT DISTINCT(energy_category_id) " |
||
| 236 | " FROM tbl_combined_equipment_input_category_hourly " |
||
| 237 | " WHERE combined_equipment_id = %s " |
||
| 238 | " AND start_datetime_utc >= %s " |
||
| 239 | " AND start_datetime_utc < %s ", |
||
| 240 | (combined_equipment['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) |
||
| 241 | rows_energy_categories = cursor_energy.fetchall() |
||
| 242 | if rows_energy_categories is not None and len(rows_energy_categories) > 0: |
||
| 243 | for row_energy_category in rows_energy_categories: |
||
| 244 | energy_category_set.add(row_energy_category[0]) |
||
| 245 | |||
| 246 | # query all energy categories in base period and reporting period |
||
| 247 | cursor_system.execute(" SELECT id, name, unit_of_measure, kgce, kgco2e " |
||
| 248 | " FROM tbl_energy_categories " |
||
| 249 | " ORDER BY id ", ) |
||
| 250 | rows_energy_categories = cursor_system.fetchall() |
||
| 251 | if rows_energy_categories is None or len(rows_energy_categories) == 0: |
||
| 252 | if cursor_system: |
||
| 253 | cursor_system.close() |
||
| 254 | if cnx_system: |
||
| 255 | cnx_system.close() |
||
| 256 | |||
| 257 | if cursor_energy: |
||
| 258 | cursor_energy.close() |
||
| 259 | if cnx_energy: |
||
| 260 | cnx_energy.close() |
||
| 261 | |||
| 262 | if cursor_historical: |
||
| 263 | cursor_historical.close() |
||
| 264 | if cnx_historical: |
||
| 265 | cnx_historical.close() |
||
| 266 | raise falcon.HTTPError(status=falcon.HTTP_404, |
||
| 267 | title='API.NOT_FOUND', |
||
| 268 | description='API.ENERGY_CATEGORY_NOT_FOUND') |
||
| 269 | energy_category_dict = dict() |
||
| 270 | for row_energy_category in rows_energy_categories: |
||
| 271 | if row_energy_category[0] in energy_category_set: |
||
| 272 | energy_category_dict[row_energy_category[0]] = {"name": row_energy_category[1], |
||
| 273 | "unit_of_measure": row_energy_category[2], |
||
| 274 | "kgce": row_energy_category[3], |
||
| 275 | "kgco2e": row_energy_category[4]} |
||
| 276 | |||
| 277 | ################################################################################################################ |
||
| 278 | # Step 4: query associated points |
||
| 279 | ################################################################################################################ |
||
| 280 | point_list = list() |
||
| 281 | cursor_system.execute(" SELECT p.id, ep.name, p.units, p.object_type " |
||
| 282 | " FROM tbl_combined_equipments e, tbl_combined_equipments_parameters ep, tbl_points p " |
||
| 283 | " WHERE e.id = %s AND e.id = ep.combined_equipment_id AND ep.parameter_type = 'point' " |
||
| 284 | " AND ep.point_id = p.id " |
||
| 285 | " ORDER BY p.id ", (combined_equipment['id'],)) |
||
| 286 | rows_points = cursor_system.fetchall() |
||
| 287 | if rows_points is not None and len(rows_points) > 0: |
||
| 288 | for row in rows_points: |
||
| 289 | point_list.append({"id": row[0], "name": row[1], "units": row[2], "object_type": row[3]}) |
||
| 290 | |||
| 291 | ################################################################################################################ |
||
| 292 | # Step 5: query associated equipments |
||
| 293 | ################################################################################################################ |
||
| 294 | associated_equipment_list = list() |
||
| 295 | cursor_system.execute(" SELECT e.id, e.name " |
||
| 296 | " FROM tbl_equipments e,tbl_combined_equipments_equipments ee" |
||
| 297 | " WHERE ee.combined_equipment_id = %s AND e.id = ee.equipment_id" |
||
| 298 | " ORDER BY id ", (combined_equipment['id'],)) |
||
| 299 | rows_associated_equipments = cursor_system.fetchall() |
||
| 300 | if rows_associated_equipments is not None and len(rows_associated_equipments) > 0: |
||
| 301 | for row in rows_associated_equipments: |
||
| 302 | associated_equipment_list.append({"id": row[0], "name": row[1]}) |
||
| 303 | |||
| 304 | ################################################################################################################ |
||
| 305 | # Step 6: query base period energy input |
||
| 306 | ################################################################################################################ |
||
| 307 | base = dict() |
||
| 308 | if energy_category_set is not None and len(energy_category_set) > 0: |
||
| 309 | for energy_category_id in energy_category_set: |
||
| 310 | base[energy_category_id] = dict() |
||
| 311 | base[energy_category_id]['timestamps'] = list() |
||
| 312 | base[energy_category_id]['values'] = list() |
||
| 313 | base[energy_category_id]['subtotal'] = Decimal(0.0) |
||
| 314 | base[energy_category_id]['mean'] = None |
||
| 315 | base[energy_category_id]['median'] = None |
||
| 316 | base[energy_category_id]['minimum'] = None |
||
| 317 | base[energy_category_id]['maximum'] = None |
||
| 318 | base[energy_category_id]['stdev'] = None |
||
| 319 | base[energy_category_id]['variance'] = None |
||
| 320 | |||
| 321 | cursor_energy.execute(" SELECT start_datetime_utc, actual_value " |
||
| 322 | " FROM tbl_combined_equipment_input_category_hourly " |
||
| 323 | " WHERE combined_equipment_id = %s " |
||
| 324 | " AND energy_category_id = %s " |
||
| 325 | " AND start_datetime_utc >= %s " |
||
| 326 | " AND start_datetime_utc < %s " |
||
| 327 | " ORDER BY start_datetime_utc ", |
||
| 328 | (combined_equipment['id'], |
||
| 329 | energy_category_id, |
||
| 330 | base_start_datetime_utc, |
||
| 331 | base_end_datetime_utc)) |
||
| 332 | rows_combined_equipment_hourly = cursor_energy.fetchall() |
||
| 333 | |||
| 334 | rows_combined_equipment_periodically, \ |
||
| 335 | base[energy_category_id]['mean'], \ |
||
| 336 | base[energy_category_id]['median'], \ |
||
| 337 | base[energy_category_id]['minimum'], \ |
||
| 338 | base[energy_category_id]['maximum'], \ |
||
| 339 | base[energy_category_id]['stdev'], \ |
||
| 340 | base[energy_category_id]['variance'] = \ |
||
| 341 | utilities.statistics_hourly_data_by_period(rows_combined_equipment_hourly, |
||
| 342 | base_start_datetime_utc, |
||
| 343 | base_end_datetime_utc, |
||
| 344 | period_type) |
||
| 345 | |||
| 346 | for row_combined_equipment_periodically in rows_combined_equipment_periodically: |
||
| 347 | current_datetime_local = row_combined_equipment_periodically[0].replace(tzinfo=timezone.utc) + \ |
||
| 348 | timedelta(minutes=timezone_offset) |
||
| 349 | if period_type == 'hourly': |
||
| 350 | current_datetime = current_datetime_local.isoformat()[0:19] |
||
| 351 | elif period_type == 'daily': |
||
| 352 | current_datetime = current_datetime_local.isoformat()[0:10] |
||
| 353 | elif period_type == 'weekly': |
||
| 354 | current_datetime = current_datetime_local.isoformat()[0:10] |
||
| 355 | elif period_type == 'monthly': |
||
| 356 | current_datetime = current_datetime_local.isoformat()[0:7] |
||
| 357 | elif period_type == 'yearly': |
||
| 358 | current_datetime = current_datetime_local.isoformat()[0:4] |
||
| 359 | |||
| 360 | actual_value = Decimal(0.0) if row_combined_equipment_periodically[1] is None \ |
||
| 361 | else row_combined_equipment_periodically[1] |
||
| 362 | base[energy_category_id]['timestamps'].append(current_datetime) |
||
| 363 | base[energy_category_id]['values'].append(actual_value) |
||
| 364 | base[energy_category_id]['subtotal'] += actual_value |
||
| 365 | |||
| 366 | ################################################################################################################ |
||
| 367 | # Step 7: query reporting period energy input |
||
| 368 | ################################################################################################################ |
||
| 369 | reporting = dict() |
||
| 370 | if energy_category_set is not None and len(energy_category_set) > 0: |
||
| 371 | for energy_category_id in energy_category_set: |
||
| 372 | reporting[energy_category_id] = dict() |
||
| 373 | reporting[energy_category_id]['timestamps'] = list() |
||
| 374 | reporting[energy_category_id]['values'] = list() |
||
| 375 | reporting[energy_category_id]['subtotal'] = Decimal(0.0) |
||
| 376 | reporting[energy_category_id]['mean'] = None |
||
| 377 | reporting[energy_category_id]['median'] = None |
||
| 378 | reporting[energy_category_id]['minimum'] = None |
||
| 379 | reporting[energy_category_id]['maximum'] = None |
||
| 380 | reporting[energy_category_id]['stdev'] = None |
||
| 381 | reporting[energy_category_id]['variance'] = None |
||
| 382 | |||
| 383 | cursor_energy.execute(" SELECT start_datetime_utc, actual_value " |
||
| 384 | " FROM tbl_combined_equipment_input_category_hourly " |
||
| 385 | " WHERE combined_equipment_id = %s " |
||
| 386 | " AND energy_category_id = %s " |
||
| 387 | " AND start_datetime_utc >= %s " |
||
| 388 | " AND start_datetime_utc < %s " |
||
| 389 | " ORDER BY start_datetime_utc ", |
||
| 390 | (combined_equipment['id'], |
||
| 391 | energy_category_id, |
||
| 392 | reporting_start_datetime_utc, |
||
| 393 | reporting_end_datetime_utc)) |
||
| 394 | rows_combined_equipment_hourly = cursor_energy.fetchall() |
||
| 395 | |||
| 396 | rows_combined_equipment_periodically, \ |
||
| 397 | reporting[energy_category_id]['mean'], \ |
||
| 398 | reporting[energy_category_id]['median'], \ |
||
| 399 | reporting[energy_category_id]['minimum'], \ |
||
| 400 | reporting[energy_category_id]['maximum'], \ |
||
| 401 | reporting[energy_category_id]['stdev'], \ |
||
| 402 | reporting[energy_category_id]['variance'] = \ |
||
| 403 | utilities.statistics_hourly_data_by_period(rows_combined_equipment_hourly, |
||
| 404 | reporting_start_datetime_utc, |
||
| 405 | reporting_end_datetime_utc, |
||
| 406 | period_type) |
||
| 407 | |||
| 408 | for row_combined_equipment_periodically in rows_combined_equipment_periodically: |
||
| 409 | current_datetime_local = row_combined_equipment_periodically[0].replace(tzinfo=timezone.utc) + \ |
||
| 410 | timedelta(minutes=timezone_offset) |
||
| 411 | if period_type == 'hourly': |
||
| 412 | current_datetime = current_datetime_local.isoformat()[0:19] |
||
| 413 | elif period_type == 'daily': |
||
| 414 | current_datetime = current_datetime_local.isoformat()[0:10] |
||
| 415 | elif period_type == 'weekly': |
||
| 416 | current_datetime = current_datetime_local.isoformat()[0:10] |
||
| 417 | elif period_type == 'monthly': |
||
| 418 | current_datetime = current_datetime_local.isoformat()[0:7] |
||
| 419 | elif period_type == 'yearly': |
||
| 420 | current_datetime = current_datetime_local.isoformat()[0:4] |
||
| 421 | |||
| 422 | actual_value = Decimal(0.0) if row_combined_equipment_periodically[1] is None \ |
||
| 423 | else row_combined_equipment_periodically[1] |
||
| 424 | reporting[energy_category_id]['timestamps'].append(current_datetime) |
||
| 425 | reporting[energy_category_id]['values'].append(actual_value) |
||
| 426 | reporting[energy_category_id]['subtotal'] += actual_value |
||
| 427 | |||
| 428 | ################################################################################################################ |
||
| 429 | # Step 8: query tariff data |
||
| 430 | ################################################################################################################ |
||
| 431 | parameters_data = dict() |
||
| 432 | parameters_data['names'] = list() |
||
| 433 | parameters_data['timestamps'] = list() |
||
| 434 | parameters_data['values'] = list() |
||
| 435 | if not is_quick_mode: |
||
| 436 | if config.is_tariff_appended and energy_category_set is not None and len(energy_category_set) > 0: |
||
| 437 | for energy_category_id in energy_category_set: |
||
| 438 | energy_category_tariff_dict = \ |
||
| 439 | utilities.get_energy_category_tariffs(combined_equipment['cost_center_id'], |
||
| 440 | energy_category_id, |
||
| 441 | reporting_start_datetime_utc, |
||
| 442 | reporting_end_datetime_utc) |
||
| 443 | tariff_timestamp_list = list() |
||
| 444 | tariff_value_list = list() |
||
| 445 | for k, v in energy_category_tariff_dict.items(): |
||
| 446 | # convert k from utc to local |
||
| 447 | k = k + timedelta(minutes=timezone_offset) |
||
| 448 | tariff_timestamp_list.append(k.isoformat()[0:19]) |
||
| 449 | tariff_value_list.append(v) |
||
| 450 | |||
| 451 | parameters_data['names'].append( |
||
| 452 | _('Tariff') + '-' + energy_category_dict[energy_category_id]['name']) |
||
| 453 | parameters_data['timestamps'].append(tariff_timestamp_list) |
||
| 454 | parameters_data['values'].append(tariff_value_list) |
||
| 455 | |||
| 456 | ################################################################################################################ |
||
| 457 | # Step 9: query associated points data |
||
| 458 | ################################################################################################################ |
||
| 459 | if not is_quick_mode: |
||
| 460 | for point in point_list: |
||
| 461 | point_values = [] |
||
| 462 | point_timestamps = [] |
||
| 463 | if point['object_type'] == 'ENERGY_VALUE': |
||
| 464 | query = (" SELECT utc_date_time, actual_value " |
||
| 465 | " FROM tbl_energy_value " |
||
| 466 | " WHERE point_id = %s " |
||
| 467 | " AND utc_date_time BETWEEN %s AND %s " |
||
| 468 | " ORDER BY utc_date_time ") |
||
| 469 | cursor_historical.execute(query, (point['id'], |
||
| 470 | reporting_start_datetime_utc, |
||
| 471 | reporting_end_datetime_utc)) |
||
| 472 | rows = cursor_historical.fetchall() |
||
| 473 | |||
| 474 | if rows is not None and len(rows) > 0: |
||
| 475 | for row in rows: |
||
| 476 | current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ |
||
| 477 | timedelta(minutes=timezone_offset) |
||
| 478 | current_datetime = current_datetime_local.isoformat()[0:19] |
||
| 479 | point_timestamps.append(current_datetime) |
||
| 480 | point_values.append(row[1]) |
||
| 481 | elif point['object_type'] == 'ANALOG_VALUE': |
||
| 482 | query = (" SELECT utc_date_time, actual_value " |
||
| 483 | " FROM tbl_analog_value " |
||
| 484 | " WHERE point_id = %s " |
||
| 485 | " AND utc_date_time BETWEEN %s AND %s " |
||
| 486 | " ORDER BY utc_date_time ") |
||
| 487 | cursor_historical.execute(query, (point['id'], |
||
| 488 | reporting_start_datetime_utc, |
||
| 489 | reporting_end_datetime_utc)) |
||
| 490 | rows = cursor_historical.fetchall() |
||
| 491 | |||
| 492 | if rows is not None and len(rows) > 0: |
||
| 493 | for row in rows: |
||
| 494 | current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ |
||
| 495 | timedelta(minutes=timezone_offset) |
||
| 496 | current_datetime = current_datetime_local.isoformat()[0:19] |
||
| 497 | point_timestamps.append(current_datetime) |
||
| 498 | point_values.append(row[1]) |
||
| 499 | elif point['object_type'] == 'DIGITAL_VALUE': |
||
| 500 | query = (" SELECT utc_date_time, actual_value " |
||
| 501 | " FROM tbl_digital_value " |
||
| 502 | " WHERE point_id = %s " |
||
| 503 | " AND utc_date_time BETWEEN %s AND %s " |
||
| 504 | " ORDER BY utc_date_time ") |
||
| 505 | cursor_historical.execute(query, (point['id'], |
||
| 506 | reporting_start_datetime_utc, |
||
| 507 | reporting_end_datetime_utc)) |
||
| 508 | rows = cursor_historical.fetchall() |
||
| 509 | |||
| 510 | if rows is not None and len(rows) > 0: |
||
| 511 | for row in rows: |
||
| 512 | current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ |
||
| 513 | timedelta(minutes=timezone_offset) |
||
| 514 | current_datetime = current_datetime_local.isoformat()[0:19] |
||
| 515 | point_timestamps.append(current_datetime) |
||
| 516 | point_values.append(row[1]) |
||
| 517 | |||
| 518 | parameters_data['names'].append(point['name'] + ' (' + point['units'] + ')') |
||
| 519 | parameters_data['timestamps'].append(point_timestamps) |
||
| 520 | parameters_data['values'].append(point_values) |
||
| 521 | |||
| 522 | ################################################################################################################ |
||
| 523 | # Step 10: query associated equipments energy input |
||
| 524 | ################################################################################################################ |
||
| 525 | associated_equipment_data = dict() |
||
| 526 | |||
| 527 | if energy_category_set is not None and len(energy_category_set) > 0: |
||
| 528 | for energy_category_id in energy_category_set: |
||
| 529 | associated_equipment_data[energy_category_id] = dict() |
||
| 530 | associated_equipment_data[energy_category_id]['associated_equipment_names'] = list() |
||
| 531 | associated_equipment_data[energy_category_id]['subtotals'] = list() |
||
| 532 | for associated_equipment in associated_equipment_list: |
||
| 533 | associated_equipment_data[energy_category_id]['associated_equipment_names'].append( |
||
| 534 | associated_equipment['name']) |
||
| 535 | |||
| 536 | cursor_energy.execute(" SELECT SUM(actual_value) " |
||
| 537 | " FROM tbl_equipment_input_category_hourly " |
||
| 538 | " WHERE equipment_id = %s " |
||
| 539 | " AND energy_category_id = %s " |
||
| 540 | " AND start_datetime_utc >= %s " |
||
| 541 | " AND start_datetime_utc < %s ", |
||
| 542 | (associated_equipment['id'], |
||
| 543 | energy_category_id, |
||
| 544 | reporting_start_datetime_utc, |
||
| 545 | reporting_end_datetime_utc)) |
||
| 546 | row_subtotal = cursor_energy.fetchone() |
||
| 547 | |||
| 548 | subtotal = Decimal(0.0) if (row_subtotal is None or row_subtotal[0] is None) else row_subtotal[0] |
||
| 549 | associated_equipment_data[energy_category_id]['subtotals'].append(subtotal) |
||
| 550 | |||
| 551 | ################################################################################################################ |
||
| 552 | # Step 11: construct the report |
||
| 553 | ################################################################################################################ |
||
| 554 | if cursor_system: |
||
| 555 | cursor_system.close() |
||
| 556 | if cnx_system: |
||
| 557 | cnx_system.close() |
||
| 558 | |||
| 559 | if cursor_energy: |
||
| 560 | cursor_energy.close() |
||
| 561 | if cnx_energy: |
||
| 562 | cnx_energy.close() |
||
| 563 | |||
| 564 | if cursor_historical: |
||
| 565 | cursor_historical.close() |
||
| 566 | if cnx_historical: |
||
| 567 | cnx_historical.close() |
||
| 568 | |||
| 569 | result = dict() |
||
| 570 | |||
| 571 | result['combined_equipment'] = dict() |
||
| 572 | result['combined_equipment']['name'] = combined_equipment['name'] |
||
| 573 | |||
| 574 | result['base_period'] = dict() |
||
| 575 | result['base_period']['names'] = list() |
||
| 576 | result['base_period']['units'] = list() |
||
| 577 | result['base_period']['timestamps'] = list() |
||
| 578 | result['base_period']['values'] = list() |
||
| 579 | result['base_period']['subtotals'] = list() |
||
| 580 | result['base_period']['means'] = list() |
||
| 581 | result['base_period']['medians'] = list() |
||
| 582 | result['base_period']['minimums'] = list() |
||
| 583 | result['base_period']['maximums'] = list() |
||
| 584 | result['base_period']['stdevs'] = list() |
||
| 585 | result['base_period']['variances'] = list() |
||
| 586 | |||
| 587 | if energy_category_set is not None and len(energy_category_set) > 0: |
||
| 588 | for energy_category_id in energy_category_set: |
||
| 589 | result['base_period']['names'].append(energy_category_dict[energy_category_id]['name']) |
||
| 590 | result['base_period']['units'].append(energy_category_dict[energy_category_id]['unit_of_measure']) |
||
| 591 | result['base_period']['timestamps'].append(base[energy_category_id]['timestamps']) |
||
| 592 | result['base_period']['values'].append(base[energy_category_id]['values']) |
||
| 593 | result['base_period']['subtotals'].append(base[energy_category_id]['subtotal']) |
||
| 594 | result['base_period']['means'].append(base[energy_category_id]['mean']) |
||
| 595 | result['base_period']['medians'].append(base[energy_category_id]['median']) |
||
| 596 | result['base_period']['minimums'].append(base[energy_category_id]['minimum']) |
||
| 597 | result['base_period']['maximums'].append(base[energy_category_id]['maximum']) |
||
| 598 | result['base_period']['stdevs'].append(base[energy_category_id]['stdev']) |
||
| 599 | result['base_period']['variances'].append(base[energy_category_id]['variance']) |
||
| 600 | |||
| 601 | result['reporting_period'] = dict() |
||
| 602 | result['reporting_period']['names'] = list() |
||
| 603 | result['reporting_period']['energy_category_ids'] = list() |
||
| 604 | result['reporting_period']['units'] = list() |
||
| 605 | result['reporting_period']['timestamps'] = list() |
||
| 606 | result['reporting_period']['values'] = list() |
||
| 607 | result['reporting_period']['rates'] = list() |
||
| 608 | result['reporting_period']['subtotals'] = list() |
||
| 609 | result['reporting_period']['means'] = list() |
||
| 610 | result['reporting_period']['means_increment_rate'] = list() |
||
| 611 | result['reporting_period']['medians'] = list() |
||
| 612 | result['reporting_period']['medians_increment_rate'] = list() |
||
| 613 | result['reporting_period']['minimums'] = list() |
||
| 614 | result['reporting_period']['minimums_increment_rate'] = list() |
||
| 615 | result['reporting_period']['maximums'] = list() |
||
| 616 | result['reporting_period']['maximums_increment_rate'] = list() |
||
| 617 | result['reporting_period']['stdevs'] = list() |
||
| 618 | result['reporting_period']['stdevs_increment_rate'] = list() |
||
| 619 | result['reporting_period']['variances'] = list() |
||
| 620 | result['reporting_period']['variances_increment_rate'] = list() |
||
| 621 | |||
| 622 | View Code Duplication | if energy_category_set is not None and len(energy_category_set) > 0: |
|
| 623 | for energy_category_id in energy_category_set: |
||
| 624 | result['reporting_period']['names'].append(energy_category_dict[energy_category_id]['name']) |
||
| 625 | result['reporting_period']['energy_category_ids'].append(energy_category_id) |
||
| 626 | result['reporting_period']['units'].append(energy_category_dict[energy_category_id]['unit_of_measure']) |
||
| 627 | result['reporting_period']['timestamps'].append(reporting[energy_category_id]['timestamps']) |
||
| 628 | result['reporting_period']['values'].append(reporting[energy_category_id]['values']) |
||
| 629 | result['reporting_period']['subtotals'].append(reporting[energy_category_id]['subtotal']) |
||
| 630 | result['reporting_period']['means'].append(reporting[energy_category_id]['mean']) |
||
| 631 | result['reporting_period']['means_increment_rate'].append( |
||
| 632 | (reporting[energy_category_id]['mean'] - base[energy_category_id]['mean']) / |
||
| 633 | base[energy_category_id]['mean'] if (base[energy_category_id]['mean'] is not None and |
||
| 634 | base[energy_category_id]['mean'] > Decimal(0.0)) |
||
| 635 | else None) |
||
| 636 | result['reporting_period']['medians'].append(reporting[energy_category_id]['median']) |
||
| 637 | result['reporting_period']['medians_increment_rate'].append( |
||
| 638 | (reporting[energy_category_id]['median'] - base[energy_category_id]['median']) / |
||
| 639 | base[energy_category_id]['median'] if (base[energy_category_id]['median'] is not None and |
||
| 640 | base[energy_category_id]['median'] > Decimal(0.0)) |
||
| 641 | else None) |
||
| 642 | result['reporting_period']['minimums'].append(reporting[energy_category_id]['minimum']) |
||
| 643 | result['reporting_period']['minimums_increment_rate'].append( |
||
| 644 | (reporting[energy_category_id]['minimum'] - base[energy_category_id]['minimum']) / |
||
| 645 | base[energy_category_id]['minimum'] if (base[energy_category_id]['minimum'] is not None and |
||
| 646 | base[energy_category_id]['minimum'] > Decimal(0.0)) |
||
| 647 | else None) |
||
| 648 | result['reporting_period']['maximums'].append(reporting[energy_category_id]['maximum']) |
||
| 649 | result['reporting_period']['maximums_increment_rate'].append( |
||
| 650 | (reporting[energy_category_id]['maximum'] - base[energy_category_id]['maximum']) / |
||
| 651 | base[energy_category_id]['maximum'] if (base[energy_category_id]['maximum'] is not None and |
||
| 652 | base[energy_category_id]['maximum'] > Decimal(0.0)) |
||
| 653 | else None) |
||
| 654 | result['reporting_period']['stdevs'].append(reporting[energy_category_id]['stdev']) |
||
| 655 | result['reporting_period']['stdevs_increment_rate'].append( |
||
| 656 | (reporting[energy_category_id]['stdev'] - base[energy_category_id]['stdev']) / |
||
| 657 | base[energy_category_id]['stdev'] if (base[energy_category_id]['stdev'] is not None and |
||
| 658 | base[energy_category_id]['stdev'] > Decimal(0.0)) |
||
| 659 | else None) |
||
| 660 | result['reporting_period']['variances'].append(reporting[energy_category_id]['variance']) |
||
| 661 | result['reporting_period']['variances_increment_rate'].append( |
||
| 662 | (reporting[energy_category_id]['variance'] - base[energy_category_id]['variance']) / |
||
| 663 | base[energy_category_id]['variance'] if (base[energy_category_id]['variance'] is not None and |
||
| 664 | base[energy_category_id]['variance'] > Decimal(0.0)) |
||
| 665 | else None) |
||
| 666 | |||
| 667 | rate = list() |
||
| 668 | for index, value in enumerate(reporting[energy_category_id]['values']): |
||
| 669 | if index < len(base[energy_category_id]['values']) \ |
||
| 670 | and base[energy_category_id]['values'][index] != 0 and value != 0: |
||
| 671 | rate.append((value - base[energy_category_id]['values'][index]) |
||
| 672 | / base[energy_category_id]['values'][index]) |
||
| 673 | else: |
||
| 674 | rate.append(None) |
||
| 675 | result['reporting_period']['rates'].append(rate) |
||
| 676 | |||
| 677 | result['parameters'] = { |
||
| 678 | "names": parameters_data['names'], |
||
| 679 | "timestamps": parameters_data['timestamps'], |
||
| 680 | "values": parameters_data['values'] |
||
| 681 | } |
||
| 682 | |||
| 683 | result['associated_equipment'] = dict() |
||
| 684 | result['associated_equipment']['energy_category_names'] = list() |
||
| 685 | result['associated_equipment']['units'] = list() |
||
| 686 | result['associated_equipment']['associated_equipment_names_array'] = list() |
||
| 687 | result['associated_equipment']['subtotals_array'] = list() |
||
| 688 | if energy_category_set is not None and len(energy_category_set) > 0: |
||
| 689 | for energy_category_id in energy_category_set: |
||
| 690 | result['associated_equipment']['energy_category_names'].append( |
||
| 691 | energy_category_dict[energy_category_id]['name']) |
||
| 692 | result['associated_equipment']['units'].append( |
||
| 693 | energy_category_dict[energy_category_id]['unit_of_measure']) |
||
| 694 | result['associated_equipment']['associated_equipment_names_array'].append( |
||
| 695 | associated_equipment_data[energy_category_id]['associated_equipment_names']) |
||
| 696 | result['associated_equipment']['subtotals_array'].append( |
||
| 697 | associated_equipment_data[energy_category_id]['subtotals']) |
||
| 698 | |||
| 699 | # export result to Excel file and then encode the file to base64 string |
||
| 700 | result['excel_bytes_base64'] = None |
||
| 701 | if not is_quick_mode: |
||
| 702 | result['excel_bytes_base64'] = \ |
||
| 703 | excelexporters.combinedequipmentstatistics.export(result, |
||
| 704 | combined_equipment['name'], |
||
| 705 | base_period_start_datetime_local, |
||
| 706 | base_period_end_datetime_local, |
||
| 707 | reporting_period_start_datetime_local, |
||
| 708 | reporting_period_end_datetime_local, |
||
| 709 | period_type, |
||
| 710 | language) |
||
| 711 | |||
| 712 | resp.text = json.dumps(result) |
||
| 713 |
Loading history...