Issues (1656)

myems-api/reports/combinedequipmentload.py (4 issues)

1
import re
2
from datetime import datetime, timedelta, timezone
3
from decimal import Decimal
4
import falcon
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import mysql.connector
6
import simplejson as json
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import config
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import excelexporters.combinedequipmentload
9
from core import utilities
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from core.useractivity import access_control, api_key_control
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12
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class Reporting:
14
    def __init__(self):
15
        """Initializes Class"""
16
        pass
17
18
    @staticmethod
19
    def on_options(req, resp):
20
        _ = req
21
        resp.status = falcon.HTTP_200
22
23
    ####################################################################################################################
24
    # PROCEDURES
25
    # Step 1: valid parameters
26
    # Step 2: query the combined equipment
27
    # Step 3: query energy categories
28
    # Step 4: query associated points
29
    # Step 5: query associated equipments
30
    # Step 6: query base period energy input
31
    # Step 7: query reporting period energy input
32
    # Step 8: query tariff data
33
    # Step 9: query associated points data
34
    # Step 10: query associated equipments energy input
35
    # Step 11: construct the report
36
    ####################################################################################################################
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:
0 ignored issues
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The variable row_combined_equipment does not seem to be defined for all execution paths.
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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]['sub_averages'] = list()
313
                base[energy_category_id]['sub_maximums'] = list()
314
                base[energy_category_id]['average'] = None
315
                base[energy_category_id]['maximum'] = None
316
                base[energy_category_id]['factor'] = None
317
318
                cursor_energy.execute(" SELECT start_datetime_utc, actual_value "
319
                                      " FROM tbl_combined_equipment_input_category_hourly "
320
                                      " WHERE combined_equipment_id = %s "
321
                                      "     AND energy_category_id = %s "
322
                                      "     AND start_datetime_utc >= %s "
323
                                      "     AND start_datetime_utc < %s "
324
                                      " ORDER BY start_datetime_utc ",
325
                                      (combined_equipment['id'],
326
                                       energy_category_id,
327
                                       base_start_datetime_utc,
328
                                       base_end_datetime_utc))
329
                rows_combined_equipment_hourly = cursor_energy.fetchall()
330
331
                rows_combined_equipment_periodically, \
332
                    base[energy_category_id]['average'], \
333
                    base[energy_category_id]['maximum'] = \
334
                    utilities.averaging_hourly_data_by_period(rows_combined_equipment_hourly,
335
                                                              base_start_datetime_utc,
336
                                                              base_end_datetime_utc,
337
                                                              period_type)
338
                base[energy_category_id]['factor'] = \
339
                    (base[energy_category_id]['average'] / base[energy_category_id]['maximum']
340
                     if (base[energy_category_id]['average'] is not None and
341
                         base[energy_category_id]['maximum'] is not None and
342
                         base[energy_category_id]['maximum'] > Decimal(0.0))
343
                     else None)
344
345
                for row_combined_equipment_periodically in rows_combined_equipment_periodically:
346
                    current_datetime_local = row_combined_equipment_periodically[0].replace(tzinfo=timezone.utc) + \
347
                                             timedelta(minutes=timezone_offset)
348
                    if period_type == 'hourly':
349
                        current_datetime = current_datetime_local.isoformat()[0:19]
350
                    elif period_type == 'daily':
351
                        current_datetime = current_datetime_local.isoformat()[0:10]
352
                    elif period_type == 'weekly':
353
                        current_datetime = current_datetime_local.isoformat()[0:10]
354
                    elif period_type == 'monthly':
355
                        current_datetime = current_datetime_local.isoformat()[0:7]
356
                    elif period_type == 'yearly':
357
                        current_datetime = current_datetime_local.isoformat()[0:4]
358
359
                    base[energy_category_id]['timestamps'].append(current_datetime)
0 ignored issues
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The variable current_datetime does not seem to be defined for all execution paths.
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360
                    base[energy_category_id]['sub_averages'].append(row_combined_equipment_periodically[1])
361
                    base[energy_category_id]['sub_maximums'].append(row_combined_equipment_periodically[2])
362
363
        ################################################################################################################
364
        # Step 7: query reporting period energy input
365
        ################################################################################################################
366
        reporting = dict()
367
        if energy_category_set is not None and len(energy_category_set) > 0:
368
            for energy_category_id in energy_category_set:
369
                reporting[energy_category_id] = dict()
370
                reporting[energy_category_id]['timestamps'] = list()
371
                reporting[energy_category_id]['sub_averages'] = list()
372
                reporting[energy_category_id]['sub_maximums'] = list()
373
                reporting[energy_category_id]['average'] = None
374
                reporting[energy_category_id]['maximum'] = None
375
                reporting[energy_category_id]['factor'] = None
376
377
                cursor_energy.execute(" SELECT start_datetime_utc, actual_value "
378
                                      " FROM tbl_combined_equipment_input_category_hourly "
379
                                      " WHERE combined_equipment_id = %s "
380
                                      "     AND energy_category_id = %s "
381
                                      "     AND start_datetime_utc >= %s "
382
                                      "     AND start_datetime_utc < %s "
383
                                      " ORDER BY start_datetime_utc ",
384
                                      (combined_equipment['id'],
385
                                       energy_category_id,
386
                                       reporting_start_datetime_utc,
387
                                       reporting_end_datetime_utc))
388
                rows_combined_equipment_hourly = cursor_energy.fetchall()
389
390
                rows_combined_equipment_periodically, \
391
                    reporting[energy_category_id]['average'], \
392
                    reporting[energy_category_id]['maximum'] = \
393
                    utilities.averaging_hourly_data_by_period(rows_combined_equipment_hourly,
394
                                                              reporting_start_datetime_utc,
395
                                                              reporting_end_datetime_utc,
396
                                                              period_type)
397
                reporting[energy_category_id]['factor'] = \
398
                    (reporting[energy_category_id]['average'] / reporting[energy_category_id]['maximum']
399
                     if (reporting[energy_category_id]['average'] is not None and
400
                         reporting[energy_category_id]['maximum'] is not None and
401
                         reporting[energy_category_id]['maximum'] > Decimal(0.0))
402
                     else None)
403
404
                for row_combined_equipment_periodically in rows_combined_equipment_periodically:
405
                    current_datetime_local = row_combined_equipment_periodically[0].replace(tzinfo=timezone.utc) + \
406
                                             timedelta(minutes=timezone_offset)
407
                    if period_type == 'hourly':
408
                        current_datetime = current_datetime_local.isoformat()[0:19]
409
                    elif period_type == 'daily':
410
                        current_datetime = current_datetime_local.isoformat()[0:10]
411
                    elif period_type == 'weekly':
412
                        current_datetime = current_datetime_local.isoformat()[0:10]
413
                    elif period_type == 'monthly':
414
                        current_datetime = current_datetime_local.isoformat()[0:7]
415
                    elif period_type == 'yearly':
416
                        current_datetime = current_datetime_local.isoformat()[0:4]
417
418
                    reporting[energy_category_id]['timestamps'].append(current_datetime)
419
                    reporting[energy_category_id]['sub_averages'].append(row_combined_equipment_periodically[1])
420
                    reporting[energy_category_id]['sub_maximums'].append(row_combined_equipment_periodically[2])
421
422
        ################################################################################################################
423
        # Step 8: query tariff data
424
        ################################################################################################################
425
        parameters_data = dict()
426
        parameters_data['names'] = list()
427
        parameters_data['timestamps'] = list()
428
        parameters_data['values'] = list()
429
        if not is_quick_mode:
430
            if config.is_tariff_appended and energy_category_set is not None and len(energy_category_set) > 0:
431
                for energy_category_id in energy_category_set:
432
                    energy_category_tariff_dict = \
433
                        utilities.get_energy_category_tariffs(combined_equipment['cost_center_id'],
434
                                                              energy_category_id,
435
                                                              reporting_start_datetime_utc,
436
                                                              reporting_end_datetime_utc)
437
                    tariff_timestamp_list = list()
438
                    tariff_value_list = list()
439
                    for k, v in energy_category_tariff_dict.items():
440
                        # convert k from utc to local
441
                        k = k + timedelta(minutes=timezone_offset)
442
                        tariff_timestamp_list.append(k.isoformat()[0:19])
443
                        tariff_value_list.append(v)
444
445
                    parameters_data['names'].append(
446
                        _('Tariff') + '-' + energy_category_dict[energy_category_id]['name'])
447
                    parameters_data['timestamps'].append(tariff_timestamp_list)
448
                    parameters_data['values'].append(tariff_value_list)
449
450
        ################################################################################################################
451
        # Step 9: query associated points data
452
        ################################################################################################################
453
        if not is_quick_mode:
454
            for point in point_list:
455
                point_values = []
456
                point_timestamps = []
457
                if point['object_type'] == 'ENERGY_VALUE':
458
                    query = (" SELECT utc_date_time, actual_value "
459
                             " FROM tbl_energy_value "
460
                             " WHERE point_id = %s "
461
                             "       AND utc_date_time BETWEEN %s AND %s "
462
                             " ORDER BY utc_date_time ")
463
                    cursor_historical.execute(query, (point['id'],
464
                                                      reporting_start_datetime_utc,
465
                                                      reporting_end_datetime_utc))
466
                    rows = cursor_historical.fetchall()
467
468
                    if rows is not None and len(rows) > 0:
469
                        for row in rows:
470
                            current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \
471
                                                     timedelta(minutes=timezone_offset)
472
                            current_datetime = current_datetime_local.isoformat()[0:19]
473
                            point_timestamps.append(current_datetime)
474
                            point_values.append(row[1])
475
                elif point['object_type'] == 'ANALOG_VALUE':
476
                    query = (" SELECT utc_date_time, actual_value "
477
                             " FROM tbl_analog_value "
478
                             " WHERE point_id = %s "
479
                             "       AND utc_date_time BETWEEN %s AND %s "
480
                             " ORDER BY utc_date_time ")
481
                    cursor_historical.execute(query, (point['id'],
482
                                                      reporting_start_datetime_utc,
483
                                                      reporting_end_datetime_utc))
484
                    rows = cursor_historical.fetchall()
485
486
                    if rows is not None and len(rows) > 0:
487
                        for row in rows:
488
                            current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \
489
                                                     timedelta(minutes=timezone_offset)
490
                            current_datetime = current_datetime_local.isoformat()[0:19]
491
                            point_timestamps.append(current_datetime)
492
                            point_values.append(row[1])
493
                elif point['object_type'] == 'DIGITAL_VALUE':
494
                    query = (" SELECT utc_date_time, actual_value "
495
                             " FROM tbl_digital_value "
496
                             " WHERE point_id = %s "
497
                             "       AND utc_date_time BETWEEN %s AND %s "
498
                             " ORDER BY utc_date_time ")
499
                    cursor_historical.execute(query, (point['id'],
500
                                                      reporting_start_datetime_utc,
501
                                                      reporting_end_datetime_utc))
502
                    rows = cursor_historical.fetchall()
503
504
                    if rows is not None and len(rows) > 0:
505
                        for row in rows:
506
                            current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \
507
                                                     timedelta(minutes=timezone_offset)
508
                            current_datetime = current_datetime_local.isoformat()[0:19]
509
                            point_timestamps.append(current_datetime)
510
                            point_values.append(row[1])
511
512
                parameters_data['names'].append(point['name'] + ' (' + point['units'] + ')')
513
                parameters_data['timestamps'].append(point_timestamps)
514
                parameters_data['values'].append(point_values)
515
516
        ################################################################################################################
517
        # Step 10: query associated equipments energy input
518
        ################################################################################################################
519
        associated_equipment_data = dict()
520
521
        if energy_category_set is not None and len(energy_category_set) > 0:
522
            for energy_category_id in energy_category_set:
523
                associated_equipment_data[energy_category_id] = dict()
524
                associated_equipment_data[energy_category_id]['associated_equipment_names'] = list()
525
                associated_equipment_data[energy_category_id]['average'] = list()
526
                associated_equipment_data[energy_category_id]['maximum'] = list()
527
                associated_equipment_data[energy_category_id]['sub_averages'] = list()
528
                associated_equipment_data[energy_category_id]['sub_maximums'] = list()
529
                for associated_equipment in associated_equipment_list:
530
                    associated_equipment_data[energy_category_id]['associated_equipment_names'].append(
531
                        associated_equipment['name'])
532
533
                    cursor_energy.execute(" SELECT start_datetime_utc, actual_value "
534
                                          " FROM tbl_equipment_input_category_hourly "
535
                                          " WHERE equipment_id = %s "
536
                                          "     AND energy_category_id = %s "
537
                                          "     AND start_datetime_utc >= %s "
538
                                          "     AND start_datetime_utc < %s "
539
                                          " ORDER BY start_datetime_utc ",
540
                                          (associated_equipment['id'],
541
                                           energy_category_id,
542
                                           reporting_start_datetime_utc,
543
                                           reporting_end_datetime_utc))
544
                    rows_associated_equipments_hourly = cursor_energy.fetchall()
545
546
                    rows_associated_equipment_periodically, \
547
                        associated_equipment_data[energy_category_id]['average'], \
548
                        associated_equipment_data[energy_category_id]['maximum'] = \
549
                        utilities.averaging_hourly_data_by_period(rows_associated_equipments_hourly,
550
                                                                  reporting_start_datetime_utc,
551
                                                                  reporting_end_datetime_utc,
552
                                                                  period_type)
553
554
                    associated_equipment_data[energy_category_id]['sub_averages'].append(
555
                        associated_equipment_data[energy_category_id]['average'])
556
                    associated_equipment_data[energy_category_id]['sub_maximums'].append(
557
                        associated_equipment_data[energy_category_id]['maximum'])
558
559
        ################################################################################################################
560
        # Step 11: construct the report
561
        ################################################################################################################
562
        if cursor_system:
563
            cursor_system.close()
564
        if cnx_system:
565
            cnx_system.close()
566
567
        if cursor_energy:
568
            cursor_energy.close()
569
        if cnx_energy:
570
            cnx_energy.close()
571
572
        if cursor_historical:
573
            cursor_historical.close()
574
        if cnx_historical:
575
            cnx_historical.close()
576
577
        result = dict()
578
579
        result['combined_equipment'] = dict()
580
        result['combined_equipment']['name'] = combined_equipment['name']
581
582
        result['base_period'] = dict()
583
        result['base_period']['names'] = list()
584
        result['base_period']['units'] = list()
585
        result['base_period']['timestamps'] = list()
586
        result['base_period']['sub_averages'] = list()
587
        result['base_period']['sub_maximums'] = list()
588
        result['base_period']['averages'] = list()
589
        result['base_period']['maximums'] = list()
590
        result['base_period']['factors'] = list()
591
        if energy_category_set is not None and len(energy_category_set) > 0:
592
            for energy_category_id in energy_category_set:
593
                result['base_period']['names'].append(energy_category_dict[energy_category_id]['name'])
594
                result['base_period']['units'].append(energy_category_dict[energy_category_id]['unit_of_measure'])
595
                result['base_period']['timestamps'].append(base[energy_category_id]['timestamps'])
596
                result['base_period']['sub_averages'].append(base[energy_category_id]['sub_averages'])
597
                result['base_period']['sub_maximums'].append(base[energy_category_id]['sub_maximums'])
598
                result['base_period']['averages'].append(base[energy_category_id]['average'])
599
                result['base_period']['maximums'].append(base[energy_category_id]['maximum'])
600
                result['base_period']['factors'].append(base[energy_category_id]['factor'])
601
602
        result['reporting_period'] = dict()
603
        result['reporting_period']['names'] = list()
604
        result['reporting_period']['energy_category_ids'] = list()
605
        result['reporting_period']['units'] = list()
606
        result['reporting_period']['timestamps'] = list()
607
        result['reporting_period']['sub_averages'] = list()
608
        result['reporting_period']['sub_maximums'] = list()
609
        result['reporting_period']['rates_of_sub_maximums'] = list()
610
        result['reporting_period']['averages'] = list()
611
        result['reporting_period']['averages_increment_rate'] = list()
612
        result['reporting_period']['maximums'] = list()
613
        result['reporting_period']['maximums_increment_rate'] = list()
614
        result['reporting_period']['factors'] = list()
615
        result['reporting_period']['factors_increment_rate'] = list()
616
617 View Code Duplication
        if energy_category_set is not None and len(energy_category_set) > 0:
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618
            for energy_category_id in energy_category_set:
619
                result['reporting_period']['names'].append(energy_category_dict[energy_category_id]['name'])
620
                result['reporting_period']['energy_category_ids'].append(energy_category_id)
621
                result['reporting_period']['units'].append(energy_category_dict[energy_category_id]['unit_of_measure'])
622
                result['reporting_period']['timestamps'].append(reporting[energy_category_id]['timestamps'])
623
                result['reporting_period']['sub_averages'].append(reporting[energy_category_id]['sub_averages'])
624
                result['reporting_period']['sub_maximums'].append(reporting[energy_category_id]['sub_maximums'])
625
                result['reporting_period']['averages'].append(reporting[energy_category_id]['average'])
626
                result['reporting_period']['averages_increment_rate'].append(
627
                    (reporting[energy_category_id]['average'] - base[energy_category_id]['average']) /
628
                    base[energy_category_id]['average'] if (reporting[energy_category_id]['average'] is not None and
629
                                                            base[energy_category_id]['average'] is not None and
630
                                                            base[energy_category_id]['average'] > Decimal(0.0))
631
                    else None)
632
                result['reporting_period']['maximums'].append(reporting[energy_category_id]['maximum'])
633
                result['reporting_period']['maximums_increment_rate'].append(
634
                    (reporting[energy_category_id]['maximum'] - base[energy_category_id]['maximum']) /
635
                    base[energy_category_id]['maximum'] if (reporting[energy_category_id]['maximum'] is not None and
636
                                                            base[energy_category_id]['maximum'] is not None and
637
                                                            base[energy_category_id]['maximum'] > Decimal(0.0))
638
                    else None)
639
                result['reporting_period']['factors'].append(reporting[energy_category_id]['factor'])
640
                result['reporting_period']['factors_increment_rate'].append(
641
                    (reporting[energy_category_id]['factor'] - base[energy_category_id]['factor']) /
642
                    base[energy_category_id]['factor'] if (reporting[energy_category_id]['factor'] is not None and
643
                                                           base[energy_category_id]['factor'] is not None and
644
                                                           base[energy_category_id]['factor'] > Decimal(0.0))
645
                    else None)
646
647
                rate = list()
648
                for index, value in enumerate(reporting[energy_category_id]['sub_maximums']):
649
                    if index < len(base[energy_category_id]['sub_maximums']) \
650
                            and base[energy_category_id]['sub_maximums'][index] != 0 and value != 0 \
651
                            and base[energy_category_id]['sub_maximums'][index] is not None and value is not None:
652
                        rate.append((value - base[energy_category_id]['sub_maximums'][index])
653
                                    / base[energy_category_id]['sub_maximums'][index])
654
                    else:
655
                        rate.append(None)
656
                result['reporting_period']['rates_of_sub_maximums'].append(rate)
657
658
        result['parameters'] = {
659
            "names": parameters_data['names'],
660
            "timestamps": parameters_data['timestamps'],
661
            "values": parameters_data['values']
662
        }
663
664
        result['associated_equipment'] = dict()
665
        result['associated_equipment']['energy_category_names'] = list()
666
        result['associated_equipment']['units'] = list()
667
        result['associated_equipment']['associated_equipment_names_array'] = list()
668
        result['associated_equipment']['sub_averages_array'] = list()
669
        result['associated_equipment']['sub_maximums_array'] = list()
670
        if energy_category_set is not None and len(energy_category_set) > 0:
671
            for energy_category_id in energy_category_set:
672
                result['associated_equipment']['energy_category_names'].append(
673
                    energy_category_dict[energy_category_id]['name'])
674
                result['associated_equipment']['units'].append(
675
                    energy_category_dict[energy_category_id]['unit_of_measure'])
676
                result['associated_equipment']['associated_equipment_names_array'].append(
677
                    associated_equipment_data[energy_category_id]['associated_equipment_names'])
678
                result['associated_equipment']['sub_averages_array'].append(
679
                    associated_equipment_data[energy_category_id]['sub_averages'])
680
                result['associated_equipment']['sub_maximums_array'].append(
681
                    associated_equipment_data[energy_category_id]['sub_maximums'])
682
683
        # export result to Excel file and then encode the file to base64 string
684
        result['excel_bytes_base64'] = None
685
        if not is_quick_mode:
686
            result['excel_bytes_base64'] = \
687
                excelexporters.combinedequipmentload.export(result,
688
                                                            combined_equipment['name'],
689
                                                            base_period_start_datetime_local,
690
                                                            base_period_end_datetime_local,
691
                                                            reporting_period_start_datetime_local,
692
                                                            reporting_period_end_datetime_local,
693
                                                            period_type,
694
                                                            language)
695
696
        resp.text = json.dumps(result)
697