reports.spaceenergycategory   F
last analyzed

Complexity

Total Complexity 119

Size/Duplication

Total Lines 644
Duplicated Lines 6.37 %

Importance

Changes 0
Metric Value
eloc 471
dl 41
loc 644
rs 2
c 0
b 0
f 0
wmc 119

3 Methods

Rating   Name   Duplication   Size   Complexity  
A Reporting.on_options() 0 3 1
A Reporting.__init__() 0 3 1
F Reporting.on_get() 41 609 117

How to fix   Duplicated Code    Complexity   

Duplicated Code

Duplicate code is one of the most pungent code smells. A rule that is often used is to re-structure code once it is duplicated in three or more places.

Common duplication problems, and corresponding solutions are:

Complexity

 Tip:   Before tackling complexity, make sure that you eliminate any duplication first. This often can reduce the size of classes significantly.

Complex classes like reports.spaceenergycategory 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
2
import simplejson as json
3
import mysql.connector
4
import config
5
from datetime import datetime, timedelta, timezone
6
from core import utilities
7
from decimal import Decimal
8
import excelexporters.spaceenergycategory
9
10
11
class Reporting:
12
    @staticmethod
13
    def __init__():
14
        pass
15
16
    @staticmethod
17
    def on_options(req, resp):
18
        resp.status = falcon.HTTP_200
19
20
    ####################################################################################################################
21
    # PROCEDURES
22
    # Step 1: valid parameters
23
    # Step 2: query the space
24
    # Step 3: query energy categories
25
    # Step 4: query associated sensors
26
    # Step 5: query associated points
27
    # Step 6: query child spaces
28
    # Step 7: query base period energy input
29
    # Step 8: query reporting period energy input
30
    # Step 9: query tariff data
31
    # Step 10: query associated sensors and points data
32
    # Step 11: query child spaces energy input
33
    # Step 12: construct the report
34
    ####################################################################################################################
35
    @staticmethod
36
    def on_get(req, resp):
37
        print(req.params)
38
        space_id = req.params.get('spaceid')
39
        period_type = req.params.get('periodtype')
40
        base_start_datetime_local = req.params.get('baseperiodstartdatetime')
41
        base_end_datetime_local = req.params.get('baseperiodenddatetime')
42
        reporting_start_datetime_local = req.params.get('reportingperiodstartdatetime')
43
        reporting_end_datetime_local = req.params.get('reportingperiodenddatetime')
44
45
        ################################################################################################################
46
        # Step 1: valid parameters
47
        ################################################################################################################
48
        if space_id is None:
49
            raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_SPACE_ID')
50
        else:
51
            space_id = str.strip(space_id)
52
            if not space_id.isdigit() or int(space_id) <= 0:
53
                raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_SPACE_ID')
54
55
        if period_type is None:
56
            raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_PERIOD_TYPE')
57
        else:
58
            period_type = str.strip(period_type)
59
            if period_type not in ['hourly', 'daily', 'monthly', 'yearly']:
60
                raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_PERIOD_TYPE')
61
62
        timezone_offset = int(config.utc_offset[1:3]) * 60 + int(config.utc_offset[4:6])
63
        if config.utc_offset[0] == '-':
64
            timezone_offset = -timezone_offset
65
66
        base_start_datetime_utc = None
67
        if base_start_datetime_local is not None and len(str.strip(base_start_datetime_local)) > 0:
68
            base_start_datetime_local = str.strip(base_start_datetime_local)
69
            try:
70
                base_start_datetime_utc = datetime.strptime(base_start_datetime_local,
71
                                                            '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \
72
                    timedelta(minutes=timezone_offset)
73
            except ValueError:
74
                raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST',
75
                                       description="API.INVALID_BASE_PERIOD_START_DATETIME")
76
77
        base_end_datetime_utc = None
78
        if base_end_datetime_local is not None and len(str.strip(base_end_datetime_local)) > 0:
79
            base_end_datetime_local = str.strip(base_end_datetime_local)
80
            try:
81
                base_end_datetime_utc = datetime.strptime(base_end_datetime_local,
82
                                                          '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \
83
                    timedelta(minutes=timezone_offset)
84
            except ValueError:
85
                raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST',
86
                                       description="API.INVALID_BASE_PERIOD_END_DATETIME")
87
88
        if base_start_datetime_utc is not None and base_end_datetime_utc is not None and \
89
                base_start_datetime_utc >= base_end_datetime_utc:
90
            raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST',
91
                                   description='API.INVALID_BASE_PERIOD_END_DATETIME')
92
93
        if reporting_start_datetime_local is None:
94
            raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST',
95
                                   description="API.INVALID_REPORTING_PERIOD_START_DATETIME")
96
        else:
97
            reporting_start_datetime_local = str.strip(reporting_start_datetime_local)
98
            try:
99
                reporting_start_datetime_utc = datetime.strptime(reporting_start_datetime_local,
100
                                                                 '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \
101
                    timedelta(minutes=timezone_offset)
102
            except ValueError:
103
                raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST',
104
                                       description="API.INVALID_REPORTING_PERIOD_START_DATETIME")
105
106
        if reporting_end_datetime_local is None:
107
            raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST',
108
                                   description="API.INVALID_REPORTING_PERIOD_END_DATETIME")
109
        else:
110
            reporting_end_datetime_local = str.strip(reporting_end_datetime_local)
111
            try:
112
                reporting_end_datetime_utc = datetime.strptime(reporting_end_datetime_local,
113
                                                               '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \
114
                    timedelta(minutes=timezone_offset)
115
            except ValueError:
116
                raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST',
117
                                       description="API.INVALID_REPORTING_PERIOD_END_DATETIME")
118
119
        if reporting_start_datetime_utc >= reporting_end_datetime_utc:
120
            raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST',
121
                                   description='API.INVALID_REPORTING_PERIOD_END_DATETIME')
122
123
        ################################################################################################################
124
        # Step 2: query the space
125
        ################################################################################################################
126
        cnx_system = mysql.connector.connect(**config.myems_system_db)
127
        cursor_system = cnx_system.cursor()
128
129
        cnx_energy = mysql.connector.connect(**config.myems_energy_db)
130
        cursor_energy = cnx_energy.cursor()
131
132
        cnx_historical = mysql.connector.connect(**config.myems_historical_db)
133
        cursor_historical = cnx_historical.cursor()
134
135
        cursor_system.execute(" SELECT id, name, area, cost_center_id "
136
                              " FROM tbl_spaces "
137
                              " WHERE id = %s ", (space_id,))
138
        row_space = cursor_system.fetchone()
139
        if row_space is None:
140
            if cursor_system:
141
                cursor_system.close()
142
            if cnx_system:
143
                cnx_system.disconnect()
144
145
            if cursor_energy:
146
                cursor_energy.close()
147
            if cnx_energy:
148
                cnx_energy.disconnect()
149
150
            if cnx_historical:
151
                cnx_historical.close()
152
            if cursor_historical:
153
                cursor_historical.disconnect()
154
            raise falcon.HTTPError(falcon.HTTP_404, title='API.NOT_FOUND', description='API.SPACE_NOT_FOUND')
155
156
        space = dict()
157
        space['id'] = row_space[0]
158
        space['name'] = row_space[1]
159
        space['area'] = row_space[2]
160
        space['cost_center_id'] = row_space[3]
161
162
        ################################################################################################################
163
        # Step 3: query energy categories
164
        ################################################################################################################
165
        energy_category_set = set()
166
        # query energy categories in base period
167
        cursor_energy.execute(" SELECT DISTINCT(energy_category_id) "
168
                              " FROM tbl_space_input_category_hourly "
169
                              " WHERE space_id = %s "
170
                              "     AND start_datetime_utc >= %s "
171
                              "     AND start_datetime_utc < %s ",
172
                              (space['id'], base_start_datetime_utc, base_end_datetime_utc))
173
        rows_energy_categories = cursor_energy.fetchall()
174
        if rows_energy_categories is not None or len(rows_energy_categories) > 0:
175
            for row_energy_category in rows_energy_categories:
176
                energy_category_set.add(row_energy_category[0])
177
178
        # query energy categories in reporting period
179
        cursor_energy.execute(" SELECT DISTINCT(energy_category_id) "
180
                              " FROM tbl_space_input_category_hourly "
181
                              " WHERE space_id = %s "
182
                              "     AND start_datetime_utc >= %s "
183
                              "     AND start_datetime_utc < %s ",
184
                              (space['id'], reporting_start_datetime_utc, reporting_end_datetime_utc))
185
        rows_energy_categories = cursor_energy.fetchall()
186
        if rows_energy_categories is not None or len(rows_energy_categories) > 0:
187
            for row_energy_category in rows_energy_categories:
188
                energy_category_set.add(row_energy_category[0])
189
190
        # query all energy categories in base period and reporting period
191
        cursor_system.execute(" SELECT id, name, unit_of_measure, kgce, kgco2e "
192
                              " FROM tbl_energy_categories "
193
                              " ORDER BY id ", )
194
        rows_energy_categories = cursor_system.fetchall()
195
        if rows_energy_categories is None or len(rows_energy_categories) == 0:
196
            if cursor_system:
197
                cursor_system.close()
198
            if cnx_system:
199
                cnx_system.disconnect()
200
201
            if cursor_energy:
202
                cursor_energy.close()
203
            if cnx_energy:
204
                cnx_energy.disconnect()
205
206
            if cnx_historical:
207
                cnx_historical.close()
208
            if cursor_historical:
209
                cursor_historical.disconnect()
210
            raise falcon.HTTPError(falcon.HTTP_404,
211
                                   title='API.NOT_FOUND',
212
                                   description='API.ENERGY_CATEGORY_NOT_FOUND')
213
        energy_category_dict = dict()
214
        for row_energy_category in rows_energy_categories:
215
            if row_energy_category[0] in energy_category_set:
216
                energy_category_dict[row_energy_category[0]] = {"name": row_energy_category[1],
217
                                                                "unit_of_measure": row_energy_category[2],
218
                                                                "kgce": row_energy_category[3],
219
                                                                "kgco2e": row_energy_category[4]}
220
221
        ################################################################################################################
222
        # Step 4: query associated sensors
223
        ################################################################################################################
224
        point_list = list()
225
        cursor_system.execute(" SELECT po.id, po.name, po.units, po.object_type  "
226
                              " FROM tbl_spaces sp, tbl_sensors se, tbl_spaces_sensors spse, "
227
                              "      tbl_points po, tbl_sensors_points sepo "
228
                              " WHERE sp.id = %s AND sp.id = spse.space_id AND spse.sensor_id = se.id "
229
                              "       AND se.id = sepo.sensor_id AND sepo.point_id = po.id "
230
                              " ORDER BY po.id ", (space['id'], ))
231
        rows_points = cursor_system.fetchall()
232
        if rows_points is not None and len(rows_points) > 0:
233
            for row in rows_points:
234
                point_list.append({"id": row[0], "name": row[1], "units": row[2], "object_type": row[3]})
235
236
        ################################################################################################################
237
        # Step 5: query associated points
238
        ################################################################################################################
239
        cursor_system.execute(" SELECT po.id, po.name, po.units, po.object_type  "
240
                              " FROM tbl_spaces sp, tbl_spaces_points sppo, tbl_points po "
241
                              " WHERE sp.id = %s AND sp.id = sppo.space_id AND sppo.point_id = po.id "
242
                              " ORDER BY po.id ", (space['id'], ))
243
        rows_points = cursor_system.fetchall()
244
        if rows_points is not None and len(rows_points) > 0:
245
            for row in rows_points:
246
                point_list.append({"id": row[0], "name": row[1], "units": row[2], "object_type": row[3]})
247
248
        ################################################################################################################
249
        # Step 6: query child spaces
250
        ################################################################################################################
251
        child_space_list = list()
252
        cursor_system.execute(" SELECT id, name  "
253
                              " FROM tbl_spaces "
254
                              " WHERE parent_space_id = %s "
255
                              " ORDER BY id ", (space['id'], ))
256
        rows_child_spaces = cursor_system.fetchall()
257
        if rows_child_spaces is not None and len(rows_child_spaces) > 0:
258
            for row in rows_child_spaces:
259
                child_space_list.append({"id": row[0], "name": row[1]})
260
261
        ################################################################################################################
262
        # Step 7: query base period energy input
263
        ################################################################################################################
264
        base = dict()
265
        if energy_category_set is not None and len(energy_category_set) > 0:
266
            for energy_category_id in energy_category_set:
267
                kgce = energy_category_dict[energy_category_id]['kgce']
268
                kgco2e = energy_category_dict[energy_category_id]['kgco2e']
269
270
                base[energy_category_id] = dict()
271
                base[energy_category_id]['timestamps'] = list()
272
                base[energy_category_id]['values'] = list()
273
                base[energy_category_id]['subtotal'] = Decimal(0.0)
274
                base[energy_category_id]['subtotal_in_kgce'] = Decimal(0.0)
275
                base[energy_category_id]['subtotal_in_kgco2e'] = Decimal(0.0)
276
277
                cursor_energy.execute(" SELECT start_datetime_utc, actual_value "
278
                                      " FROM tbl_space_input_category_hourly "
279
                                      " WHERE space_id = %s "
280
                                      "     AND energy_category_id = %s "
281
                                      "     AND start_datetime_utc >= %s "
282
                                      "     AND start_datetime_utc < %s "
283
                                      " ORDER BY start_datetime_utc ",
284
                                      (space['id'],
285
                                       energy_category_id,
286
                                       base_start_datetime_utc,
287
                                       base_end_datetime_utc))
288
                rows_space_hourly = cursor_energy.fetchall()
289
290
                rows_space_periodically = utilities.aggregate_hourly_data_by_period(rows_space_hourly,
291
                                                                                    base_start_datetime_utc,
292
                                                                                    base_end_datetime_utc,
293
                                                                                    period_type)
294
                for row_space_periodically in rows_space_periodically:
295
                    current_datetime_local = row_space_periodically[0].replace(tzinfo=timezone.utc) + \
296
                                             timedelta(minutes=timezone_offset)
297
                    if period_type == 'hourly':
298
                        current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S')
299
                    elif period_type == 'daily':
300
                        current_datetime = current_datetime_local.strftime('%Y-%m-%d')
301
                    elif period_type == 'monthly':
302
                        current_datetime = current_datetime_local.strftime('%Y-%m')
303
                    elif period_type == 'yearly':
304
                        current_datetime = current_datetime_local.strftime('%Y')
305
306
                    actual_value = Decimal(0.0) if row_space_periodically[1] is None else row_space_periodically[1]
307
                    base[energy_category_id]['timestamps'].append(current_datetime)
0 ignored issues
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308
                    base[energy_category_id]['values'].append(actual_value)
309
                    base[energy_category_id]['subtotal'] += actual_value
310
                    base[energy_category_id]['subtotal_in_kgce'] += actual_value * kgce
311
                    base[energy_category_id]['subtotal_in_kgco2e'] += actual_value * kgco2e
312
313
        ################################################################################################################
314
        # Step 8: query reporting period energy input
315
        ################################################################################################################
316
        reporting = dict()
317
        if energy_category_set is not None and len(energy_category_set) > 0:
318
            for energy_category_id in energy_category_set:
319
                kgce = energy_category_dict[energy_category_id]['kgce']
320
                kgco2e = energy_category_dict[energy_category_id]['kgco2e']
321
322
                reporting[energy_category_id] = dict()
323
                reporting[energy_category_id]['timestamps'] = list()
324
                reporting[energy_category_id]['values'] = list()
325
                reporting[energy_category_id]['subtotal'] = Decimal(0.0)
326
                reporting[energy_category_id]['subtotal_in_kgce'] = Decimal(0.0)
327
                reporting[energy_category_id]['subtotal_in_kgco2e'] = Decimal(0.0)
328
                reporting[energy_category_id]['toppeak'] = Decimal(0.0)
329
                reporting[energy_category_id]['onpeak'] = Decimal(0.0)
330
                reporting[energy_category_id]['midpeak'] = Decimal(0.0)
331
                reporting[energy_category_id]['offpeak'] = Decimal(0.0)
332
333
                cursor_energy.execute(" SELECT start_datetime_utc, actual_value "
334
                                      " FROM tbl_space_input_category_hourly "
335
                                      " WHERE space_id = %s "
336
                                      "     AND energy_category_id = %s "
337
                                      "     AND start_datetime_utc >= %s "
338
                                      "     AND start_datetime_utc < %s "
339
                                      " ORDER BY start_datetime_utc ",
340
                                      (space['id'],
341
                                       energy_category_id,
342
                                       reporting_start_datetime_utc,
343
                                       reporting_end_datetime_utc))
344
                rows_space_hourly = cursor_energy.fetchall()
345
346
                rows_space_periodically = utilities.aggregate_hourly_data_by_period(rows_space_hourly,
347
                                                                                    reporting_start_datetime_utc,
348
                                                                                    reporting_end_datetime_utc,
349
                                                                                    period_type)
350
                for row_space_periodically in rows_space_periodically:
351
                    current_datetime_local = row_space_periodically[0].replace(tzinfo=timezone.utc) + \
352
                                             timedelta(minutes=timezone_offset)
353
                    if period_type == 'hourly':
354
                        current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S')
355
                    elif period_type == 'daily':
356
                        current_datetime = current_datetime_local.strftime('%Y-%m-%d')
357
                    elif period_type == 'monthly':
358
                        current_datetime = current_datetime_local.strftime('%Y-%m')
359
                    elif period_type == 'yearly':
360
                        current_datetime = current_datetime_local.strftime('%Y')
361
362
                    actual_value = Decimal(0.0) if row_space_periodically[1] is None else row_space_periodically[1]
363
                    reporting[energy_category_id]['timestamps'].append(current_datetime)
364
                    reporting[energy_category_id]['values'].append(actual_value)
365
                    reporting[energy_category_id]['subtotal'] += actual_value
366
                    reporting[energy_category_id]['subtotal_in_kgce'] += actual_value * kgce
367
                    reporting[energy_category_id]['subtotal_in_kgco2e'] += actual_value * kgco2e
368
369
                energy_category_tariff_dict = utilities.get_energy_category_peak_types(space['cost_center_id'],
370
                                                                                       energy_category_id,
371
                                                                                       reporting_start_datetime_utc,
372
                                                                                       reporting_end_datetime_utc)
373
                for row in rows_space_hourly:
374
                    peak_type = energy_category_tariff_dict.get(row[0], None)
375
                    if peak_type == 'toppeak':
376
                        reporting[energy_category_id]['toppeak'] += row[1]
377
                    elif peak_type == 'onpeak':
378
                        reporting[energy_category_id]['onpeak'] += row[1]
379
                    elif peak_type == 'midpeak':
380
                        reporting[energy_category_id]['midpeak'] += row[1]
381
                    elif peak_type == 'offpeak':
382
                        reporting[energy_category_id]['offpeak'] += row[1]
383
384
        ################################################################################################################
385
        # Step 9: query tariff data
386
        ################################################################################################################
387
        parameters_data = dict()
388
        parameters_data['names'] = list()
389
        parameters_data['timestamps'] = list()
390
        parameters_data['values'] = list()
391
        if energy_category_set is not None and len(energy_category_set) > 0:
392
            for energy_category_id in energy_category_set:
393
                energy_category_tariff_dict = utilities.get_energy_category_tariffs(space['cost_center_id'],
394
                                                                                    energy_category_id,
395
                                                                                    reporting_start_datetime_utc,
396
                                                                                    reporting_end_datetime_utc)
397
                tariff_timestamp_list = list()
398
                tariff_value_list = list()
399
                for k, v in energy_category_tariff_dict.items():
400
                    # convert k from utc to local
401
                    k = k + timedelta(minutes=timezone_offset)
402
                    tariff_timestamp_list.append(k.isoformat()[0:19][0:19])
403
                    tariff_value_list.append(v)
404
405
                parameters_data['names'].append('TARIFF-' + energy_category_dict[energy_category_id]['name'])
406
                parameters_data['timestamps'].append(tariff_timestamp_list)
407
                parameters_data['values'].append(tariff_value_list)
408
409
        ################################################################################################################
410
        # Step 10: query associated sensors and points data
411
        ################################################################################################################
412
        for point in point_list:
413
            point_values = []
414
            point_timestamps = []
415
            if point['object_type'] == 'ANALOG_VALUE':
416
                query = (" SELECT utc_date_time, actual_value "
417
                         " FROM tbl_analog_value "
418
                         " WHERE point_id = %s "
419
                         "       AND utc_date_time BETWEEN %s AND %s "
420
                         " ORDER BY utc_date_time ")
421
                cursor_historical.execute(query, (point['id'],
422
                                                  reporting_start_datetime_utc,
423
                                                  reporting_end_datetime_utc))
424
                rows = cursor_historical.fetchall()
425
426
                if rows is not None and len(rows) > 0:
427
                    for row in rows:
428
                        current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \
429
                                                 timedelta(minutes=timezone_offset)
430
                        current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S')
431
                        point_timestamps.append(current_datetime)
432
                        point_values.append(row[1])
433
434
            elif point['object_type'] == 'ENERGY_VALUE':
435
                query = (" SELECT utc_date_time, actual_value "
436
                         " FROM tbl_energy_value "
437
                         " WHERE point_id = %s "
438
                         "       AND utc_date_time BETWEEN %s AND %s "
439
                         " ORDER BY utc_date_time ")
440
                cursor_historical.execute(query, (point['id'],
441
                                                  reporting_start_datetime_utc,
442
                                                  reporting_end_datetime_utc))
443
                rows = cursor_historical.fetchall()
444
445
                if rows is not None and len(rows) > 0:
446
                    for row in rows:
447
                        current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \
448
                                                 timedelta(minutes=timezone_offset)
449
                        current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S')
450
                        point_timestamps.append(current_datetime)
451
                        point_values.append(row[1])
452
            elif point['object_type'] == 'DIGITAL_VALUE':
453
                query = (" SELECT utc_date_time, actual_value "
454
                         " FROM tbl_digital_value "
455
                         " WHERE point_id = %s "
456
                         "       AND utc_date_time BETWEEN %s AND %s ")
457
                cursor_historical.execute(query, (point['id'],
458
                                                  reporting_start_datetime_utc,
459
                                                  reporting_end_datetime_utc))
460
                rows = cursor_historical.fetchall()
461
462
                if rows is not None and len(rows) > 0:
463
                    for row in rows:
464
                        current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \
465
                                                 timedelta(minutes=timezone_offset)
466
                        current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S')
467
                        point_timestamps.append(current_datetime)
468
                        point_values.append(row[1])
469
470
            parameters_data['names'].append(point['name'] + ' (' + point['units'] + ')')
471
            parameters_data['timestamps'].append(point_timestamps)
472
            parameters_data['values'].append(point_values)
473
474
        ################################################################################################################
475
        # Step 11: query child spaces energy input
476
        ################################################################################################################
477
        child_space_data = dict()
478
479 View Code Duplication
        if energy_category_set is not None and len(energy_category_set) > 0:
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480
            for energy_category_id in energy_category_set:
481
                child_space_data[energy_category_id] = dict()
482
                child_space_data[energy_category_id]['child_space_names'] = list()
483
                child_space_data[energy_category_id]['subtotals'] = list()
484
                child_space_data[energy_category_id]['subtotals_in_kgce'] = list()
485
                child_space_data[energy_category_id]['subtotals_in_kgco2e'] = list()
486
                kgce = energy_category_dict[energy_category_id]['kgce']
487
                kgco2e = energy_category_dict[energy_category_id]['kgco2e']
488
                for child_space in child_space_list:
489
                    child_space_data[energy_category_id]['child_space_names'].append(child_space['name'])
490
491
                    cursor_energy.execute(" SELECT SUM(actual_value) "
492
                                          " FROM tbl_space_input_category_hourly "
493
                                          " WHERE space_id = %s "
494
                                          "     AND energy_category_id = %s "
495
                                          "     AND start_datetime_utc >= %s "
496
                                          "     AND start_datetime_utc < %s "
497
                                          " ORDER BY start_datetime_utc ",
498
                                          (child_space['id'],
499
                                           energy_category_id,
500
                                           reporting_start_datetime_utc,
501
                                           reporting_end_datetime_utc))
502
                    row_subtotal = cursor_energy.fetchone()
503
504
                    subtotal = Decimal(0.0) if (row_subtotal is None or row_subtotal[0] is None) else row_subtotal[0]
505
                    child_space_data[energy_category_id]['subtotals'].append(subtotal)
506
                    child_space_data[energy_category_id]['subtotals_in_kgce'].append(subtotal * kgce)
507
                    child_space_data[energy_category_id]['subtotals_in_kgco2e'].append(subtotal * kgco2e)
508
509
        ################################################################################################################
510
        # Step 12: construct the report
511
        ################################################################################################################
512
        if cursor_system:
513
            cursor_system.close()
514
        if cnx_system:
515
            cnx_system.disconnect()
516
517
        if cursor_energy:
518
            cursor_energy.close()
519
        if cnx_energy:
520
            cnx_energy.disconnect()
521
522
        result = dict()
523
524
        result['space'] = dict()
525
        result['space']['name'] = space['name']
526
        result['space']['area'] = space['area']
527
528
        result['base_period'] = dict()
529
        result['base_period']['names'] = list()
530
        result['base_period']['units'] = list()
531
        result['base_period']['timestamps'] = list()
532
        result['base_period']['values'] = list()
533
        result['base_period']['subtotals'] = list()
534
        result['base_period']['subtotals_in_kgce'] = list()
535
        result['base_period']['subtotals_in_kgco2e'] = list()
536
        result['base_period']['total_in_kgce'] = Decimal(0.0)
537
        result['base_period']['total_in_kgco2e'] = Decimal(0.0)
538
        if energy_category_set is not None and len(energy_category_set) > 0:
539
            for energy_category_id in energy_category_set:
540
                result['base_period']['names'].append(energy_category_dict[energy_category_id]['name'])
541
                result['base_period']['units'].append(energy_category_dict[energy_category_id]['unit_of_measure'])
542
                result['base_period']['timestamps'].append(base[energy_category_id]['timestamps'])
543
                result['base_period']['values'].append(base[energy_category_id]['values'])
544
                result['base_period']['subtotals'].append(base[energy_category_id]['subtotal'])
545
                result['base_period']['subtotals_in_kgce'].append(base[energy_category_id]['subtotal_in_kgce'])
546
                result['base_period']['subtotals_in_kgco2e'].append(base[energy_category_id]['subtotal_in_kgco2e'])
547
                result['base_period']['total_in_kgce'] += base[energy_category_id]['subtotal_in_kgce']
548
                result['base_period']['total_in_kgco2e'] += base[energy_category_id]['subtotal_in_kgco2e']
549
550
        result['reporting_period'] = dict()
551
        result['reporting_period']['names'] = list()
552
        result['reporting_period']['energy_category_ids'] = list()
553
        result['reporting_period']['units'] = list()
554
        result['reporting_period']['timestamps'] = list()
555
        result['reporting_period']['values'] = list()
556
        result['reporting_period']['subtotals'] = list()
557
        result['reporting_period']['subtotals_in_kgce'] = list()
558
        result['reporting_period']['subtotals_in_kgco2e'] = list()
559
        result['reporting_period']['subtotals_per_unit_area'] = list()
560
        result['reporting_period']['toppeaks'] = list()
561
        result['reporting_period']['onpeaks'] = list()
562
        result['reporting_period']['midpeaks'] = list()
563
        result['reporting_period']['offpeaks'] = list()
564
        result['reporting_period']['increment_rates'] = list()
565
        result['reporting_period']['total_in_kgce'] = Decimal(0.0)
566
        result['reporting_period']['total_in_kgco2e'] = Decimal(0.0)
567
        result['reporting_period']['increment_rate_in_kgce'] = Decimal(0.0)
568
        result['reporting_period']['increment_rate_in_kgco2e'] = Decimal(0.0)
569
570
        if energy_category_set is not None and len(energy_category_set) > 0:
571
            for energy_category_id in energy_category_set:
572
                result['reporting_period']['names'].append(energy_category_dict[energy_category_id]['name'])
573
                result['reporting_period']['energy_category_ids'].append(energy_category_id)
574
                result['reporting_period']['units'].append(energy_category_dict[energy_category_id]['unit_of_measure'])
575
                result['reporting_period']['timestamps'].append(reporting[energy_category_id]['timestamps'])
576
                result['reporting_period']['values'].append(reporting[energy_category_id]['values'])
577
                result['reporting_period']['subtotals'].append(reporting[energy_category_id]['subtotal'])
578
                result['reporting_period']['subtotals_in_kgce'].append(
579
                    reporting[energy_category_id]['subtotal_in_kgce'])
580
                result['reporting_period']['subtotals_in_kgco2e'].append(
581
                    reporting[energy_category_id]['subtotal_in_kgco2e'])
582
                result['reporting_period']['subtotals_per_unit_area'].append(
583
                    reporting[energy_category_id]['subtotal'] / space['area'] if space['area'] > 0.0 else None)
584
                result['reporting_period']['toppeaks'].append(reporting[energy_category_id]['toppeak'])
585
                result['reporting_period']['onpeaks'].append(reporting[energy_category_id]['onpeak'])
586
                result['reporting_period']['midpeaks'].append(reporting[energy_category_id]['midpeak'])
587
                result['reporting_period']['offpeaks'].append(reporting[energy_category_id]['offpeak'])
588
                result['reporting_period']['increment_rates'].append(
589
                    (reporting[energy_category_id]['subtotal'] - base[energy_category_id]['subtotal']) /
590
                    base[energy_category_id]['subtotal']
591
                    if base[energy_category_id]['subtotal'] > 0.0 else None)
592
                result['reporting_period']['total_in_kgce'] += reporting[energy_category_id]['subtotal_in_kgce']
593
                result['reporting_period']['total_in_kgco2e'] += reporting[energy_category_id]['subtotal_in_kgco2e']
594
595
        result['reporting_period']['total_in_kgco2e_per_unit_area'] = \
596
            result['reporting_period']['total_in_kgce'] / space['area'] if space['area'] > 0.0 else None
597
598
        result['reporting_period']['increment_rate_in_kgce'] = \
599
            (result['reporting_period']['total_in_kgce'] - result['base_period']['total_in_kgce']) / \
600
            result['base_period']['total_in_kgce'] \
601
            if result['base_period']['total_in_kgce'] > Decimal(0.0) else None
602
603
        result['reporting_period']['total_in_kgce_per_unit_area'] = \
604
            result['reporting_period']['total_in_kgco2e'] / space['area'] if space['area'] > 0.0 else None
605
606
        result['reporting_period']['increment_rate_in_kgco2e'] = \
607
            (result['reporting_period']['total_in_kgco2e'] - result['base_period']['total_in_kgco2e']) / \
608
            result['base_period']['total_in_kgco2e'] \
609
            if result['base_period']['total_in_kgco2e'] > Decimal(0.0) else None
610
611
        result['parameters'] = {
612
            "names": parameters_data['names'],
613
            "timestamps": parameters_data['timestamps'],
614
            "values": parameters_data['values']
615
        }
616
617
        result['child_space'] = dict()
618
        result['child_space']['energy_category_names'] = list()  # 1D array [energy category]
619
        result['child_space']['units'] = list()  # 1D array [energy category]
620
        result['child_space']['child_space_names_array'] = list()  # 2D array [energy category][child space]
621
        result['child_space']['subtotals_array'] = list()  # 2D array [energy category][child space]
622
        result['child_space']['subtotals_in_kgce_array'] = list()  # 2D array [energy category][child space]
623
        result['child_space']['subtotals_in_kgco2e_array'] = list()  # 2D array [energy category][child space]
624 View Code Duplication
        if energy_category_set is not None and len(energy_category_set) > 0:
0 ignored issues
show
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This code seems to be duplicated in your project.
Loading history...
625
            for energy_category_id in energy_category_set:
626
                result['child_space']['energy_category_names'].append(energy_category_dict[energy_category_id]['name'])
627
                result['child_space']['units'].append(energy_category_dict[energy_category_id]['unit_of_measure'])
628
                result['child_space']['child_space_names_array'].append(
629
                    child_space_data[energy_category_id]['child_space_names'])
630
                result['child_space']['subtotals_array'].append(
631
                    child_space_data[energy_category_id]['subtotals'])
632
                result['child_space']['subtotals_in_kgce_array'].append(
633
                    child_space_data[energy_category_id]['subtotals_in_kgce'])
634
                result['child_space']['subtotals_in_kgco2e_array'].append(
635
                    child_space_data[energy_category_id]['subtotals_in_kgco2e'])
636
        # export result to Excel file and then encode the file to base64 string
637
        result['excel_bytes_base64'] = excelexporters.spaceenergycategory.export(result,
638
                                                                                 space['name'],
639
                                                                                 reporting_start_datetime_local,
640
                                                                                 reporting_end_datetime_local,
641
                                                                                 period_type)
642
643
        resp.body = json.dumps(result)
644