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reports.storesaving.Reporting.on_get()   F

Complexity

Conditions 121

Size

Total Lines 648
Code Lines 487

Duplication

Lines 648
Ratio 100 %

Importance

Changes 0
Metric Value
cc 121
eloc 487
nop 2
dl 648
loc 648
rs 0
c 0
b 0
f 0

How to fix   Long Method    Complexity   

Long Method

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:

Complexity

Complex classes like reports.storesaving.Reporting.on_get() often do a lot of different things. To break such a class down, we need to identify a cohesive component within that class. A common approach to find such a component is to look for fields/methods that share the same prefixes, or suffixes.

Once you have determined the fields that belong together, you can apply the Extract Class refactoring. If the component makes sense as a sub-class, Extract Subclass is also a candidate, and is often faster.

1
import falcon
2
import simplejson as json
3
import mysql.connector
4
import config
5
from datetime import datetime, timedelta, timezone
6
import utilities
7
from decimal import *
8
9
10 View Code Duplication
class Reporting:
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11
    @staticmethod
12
    def __init__():
13
        pass
14
15
    @staticmethod
16
    def on_options(req, resp):
17
        resp.status = falcon.HTTP_200
18
19
    ####################################################################################################################
20
    # PROCEDURES
21
    # Step 1: valid parameters
22
    # Step 2: query the store
23
    # Step 3: query energy categories
24
    # Step 4: query associated sensors
25
    # Step 5: query associated points
26
    # Step 6: query base period energy saving
27
    # Step 7: query reporting period energy saving
28
    # Step 8: query tariff data
29
    # Step 9: query associated sensors and points data
30
    # Step 10: construct the report
31
    ####################################################################################################################
32
    @staticmethod
33
    def on_get(req, resp):
34
        print(req.params)
35
        store_id = req.params.get('storeid')
36
        period_type = req.params.get('periodtype')
37
        base_start_datetime_local = req.params.get('baseperiodstartdatetime')
38
        base_end_datetime_local = req.params.get('baseperiodenddatetime')
39
        reporting_start_datetime_local = req.params.get('reportingperiodstartdatetime')
40
        reporting_end_datetime_local = req.params.get('reportingperiodenddatetime')
41
42
        ################################################################################################################
43
        # Step 1: valid parameters
44
        ################################################################################################################
45
        if store_id is None:
46
            raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_STORE_ID')
47
        else:
48
            store_id = str.strip(store_id)
49
            if not store_id.isdigit() or int(store_id) <= 0:
50
                raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_STORE_ID')
51
52
        if period_type is None:
53
            raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_PERIOD_TYPE')
54
        else:
55
            period_type = str.strip(period_type)
56
            if period_type not in ['hourly', 'daily', 'monthly', 'yearly']:
57
                raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_PERIOD_TYPE')
58
59
        timezone_offset = int(config.utc_offset[1:3]) * 60 + int(config.utc_offset[4:6])
60
        if config.utc_offset[0] == '-':
61
            timezone_offset = -timezone_offset
62
63
        base_start_datetime_utc = None
64
        if base_start_datetime_local is not None and len(str.strip(base_start_datetime_local)) > 0:
65
            base_start_datetime_local = str.strip(base_start_datetime_local)
66
            try:
67
                base_start_datetime_utc = datetime.strptime(base_start_datetime_local,
68
                                                            '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \
69
                    timedelta(minutes=timezone_offset)
70
            except ValueError:
71
                raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST',
72
                                       description="API.INVALID_BASE_PERIOD_BEGINS_DATETIME")
73
74
        base_end_datetime_utc = None
75
        if base_end_datetime_local is not None and len(str.strip(base_end_datetime_local)) > 0:
76
            base_end_datetime_local = str.strip(base_end_datetime_local)
77
            try:
78
                base_end_datetime_utc = datetime.strptime(base_end_datetime_local,
79
                                                          '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \
80
                    timedelta(minutes=timezone_offset)
81
            except ValueError:
82
                raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST',
83
                                       description="API.INVALID_BASE_PERIOD_ENDS_DATETIME")
84
85
        if base_start_datetime_utc is not None and base_end_datetime_utc is not None and \
86
                base_start_datetime_utc >= base_end_datetime_utc:
87
            raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST',
88
                                   description='API.INVALID_BASE_PERIOD_ENDS_DATETIME')
89
90
        if reporting_start_datetime_local is None:
91
            raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST',
92
                                   description="API.INVALID_REPORTING_PERIOD_BEGINS_DATETIME")
93
        else:
94
            reporting_start_datetime_local = str.strip(reporting_start_datetime_local)
95
            try:
96
                reporting_start_datetime_utc = datetime.strptime(reporting_start_datetime_local,
97
                                                                 '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \
98
                    timedelta(minutes=timezone_offset)
99
            except ValueError:
100
                raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST',
101
                                       description="API.INVALID_REPORTING_PERIOD_BEGINS_DATETIME")
102
103
        if reporting_end_datetime_local is None:
104
            raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST',
105
                                   description="API.INVALID_REPORTING_PERIOD_ENDS_DATETIME")
106
        else:
107
            reporting_end_datetime_local = str.strip(reporting_end_datetime_local)
108
            try:
109
                reporting_end_datetime_utc = datetime.strptime(reporting_end_datetime_local,
110
                                                               '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \
111
                    timedelta(minutes=timezone_offset)
112
            except ValueError:
113
                raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST',
114
                                       description="API.INVALID_REPORTING_PERIOD_ENDS_DATETIME")
115
116
        if reporting_start_datetime_utc >= reporting_end_datetime_utc:
117
            raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST',
118
                                   description='API.INVALID_REPORTING_PERIOD_ENDS_DATETIME')
119
120
        ################################################################################################################
121
        # Step 2: query the store
122
        ################################################################################################################
123
        cnx_system = mysql.connector.connect(**config.myems_system_db)
124
        cursor_system = cnx_system.cursor()
125
126
        cnx_energy = mysql.connector.connect(**config.myems_energy_db)
127
        cursor_energy = cnx_energy.cursor()
128
129
        cnx_energy_baseline = mysql.connector.connect(**config.myems_energy_baseline_db)
130
        cursor_energy_baseline = cnx_energy_baseline.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_stores "
137
                              " WHERE id = %s ", (store_id,))
138
        row_store = cursor_system.fetchone()
139
        if row_store 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 cursor_energy_baseline:
151
                cursor_energy_baseline.close()
152
            if cnx_energy_baseline:
153
                cnx_energy_baseline.disconnect()
154
155
            if cnx_historical:
156
                cnx_historical.close()
157
            if cursor_historical:
158
                cursor_historical.disconnect()
159
            raise falcon.HTTPError(falcon.HTTP_404, title='API.NOT_FOUND', description='API.STORE_NOT_FOUND')
160
161
        store = dict()
162
        store['id'] = row_store[0]
163
        store['name'] = row_store[1]
164
        store['area'] = row_store[2]
165
        store['cost_center_id'] = row_store[3]
166
167
        ################################################################################################################
168
        # Step 3: query energy categories
169
        ################################################################################################################
170
        energy_category_set = set()
171
        # query energy categories in base period
172
        cursor_energy.execute(" SELECT DISTINCT(energy_category_id) "
173
                              " FROM tbl_store_input_category_hourly "
174
                              " WHERE store_id = %s "
175
                              "     AND start_datetime_utc >= %s "
176
                              "     AND start_datetime_utc < %s ",
177
                              (store['id'], base_start_datetime_utc, base_end_datetime_utc))
178
        rows_energy_categories = cursor_energy.fetchall()
179
        if rows_energy_categories is not None or len(rows_energy_categories) > 0:
180
            for row_energy_category in rows_energy_categories:
181
                energy_category_set.add(row_energy_category[0])
182
183
        # query energy categories in reporting period
184
        cursor_energy.execute(" SELECT DISTINCT(energy_category_id) "
185
                              " FROM tbl_store_input_category_hourly "
186
                              " WHERE store_id = %s "
187
                              "     AND start_datetime_utc >= %s "
188
                              "     AND start_datetime_utc < %s ",
189
                              (store['id'], reporting_start_datetime_utc, reporting_end_datetime_utc))
190
        rows_energy_categories = cursor_energy.fetchall()
191
        if rows_energy_categories is not None or len(rows_energy_categories) > 0:
192
            for row_energy_category in rows_energy_categories:
193
                energy_category_set.add(row_energy_category[0])
194
195
        # query all energy categories in base period and reporting period
196
        cursor_system.execute(" SELECT id, name, unit_of_measure, kgce, kgco2e "
197
                              " FROM tbl_energy_categories "
198
                              " ORDER BY id ", )
199
        rows_energy_categories = cursor_system.fetchall()
200
        if rows_energy_categories is None or len(rows_energy_categories) == 0:
201
            if cursor_system:
202
                cursor_system.close()
203
            if cnx_system:
204
                cnx_system.disconnect()
205
206
            if cursor_energy:
207
                cursor_energy.close()
208
            if cnx_energy:
209
                cnx_energy.disconnect()
210
211
            if cursor_energy_baseline:
212
                cursor_energy_baseline.close()
213
            if cnx_energy_baseline:
214
                cnx_energy_baseline.disconnect()
215
216
            if cnx_historical:
217
                cnx_historical.close()
218
            if cursor_historical:
219
                cursor_historical.disconnect()
220
            raise falcon.HTTPError(falcon.HTTP_404,
221
                                   title='API.NOT_FOUND',
222
                                   description='API.ENERGY_CATEGORY_NOT_FOUND')
223
        energy_category_dict = dict()
224
        for row_energy_category in rows_energy_categories:
225
            if row_energy_category[0] in energy_category_set:
226
                energy_category_dict[row_energy_category[0]] = {"name": row_energy_category[1],
227
                                                                "unit_of_measure": row_energy_category[2],
228
                                                                "kgce": row_energy_category[3],
229
                                                                "kgco2e": row_energy_category[4]}
230
231
        ################################################################################################################
232
        # Step 4: query associated sensors
233
        ################################################################################################################
234
        point_list = list()
235
        cursor_system.execute(" SELECT p.id, p.name, p.units, p.object_type  "
236
                              " FROM tbl_stores st, tbl_sensors se, tbl_stores_sensors ss, "
237
                              "      tbl_points p, tbl_sensors_points sp "
238
                              " WHERE st.id = %s AND st.id = ss.store_id AND ss.sensor_id = se.id "
239
                              "       AND se.id = sp.sensor_id AND sp.point_id = p.id "
240
                              " ORDER BY p.id ", (store['id'],))
241
        rows_points = cursor_system.fetchall()
242
        if rows_points is not None and len(rows_points) > 0:
243
            for row in rows_points:
244
                point_list.append({"id": row[0], "name": row[1], "units": row[2], "object_type": row[3]})
245
246
        ################################################################################################################
247
        # Step 5: query associated points
248
        ################################################################################################################
249
        cursor_system.execute(" SELECT p.id, p.name, p.units, p.object_type  "
250
                              " FROM tbl_stores s, tbl_stores_points sp, tbl_points p "
251
                              " WHERE s.id = %s AND s.id = sp.store_id AND sp.point_id = p.id "
252
                              " ORDER BY p.id ", (store['id'],))
253
        rows_points = cursor_system.fetchall()
254
        if rows_points is not None and len(rows_points) > 0:
255
            for row in rows_points:
256
                point_list.append({"id": row[0], "name": row[1], "units": row[2], "object_type": row[3]})
257
258
        ################################################################################################################
259
        # Step 6: query base period energy saving
260
        ################################################################################################################
261
        base = dict()
262
        if energy_category_set is not None and len(energy_category_set) > 0:
263
            for energy_category_id in energy_category_set:
264
                kgce = energy_category_dict[energy_category_id]['kgce']
265
                kgco2e = energy_category_dict[energy_category_id]['kgco2e']
266
267
                base[energy_category_id] = dict()
268
                base[energy_category_id]['timestamps'] = list()
269
                base[energy_category_id]['values_baseline'] = list()
270
                base[energy_category_id]['values_actual'] = list()
271
                base[energy_category_id]['values_saving'] = list()
272
                base[energy_category_id]['subtotal_baseline'] = Decimal(0.0)
273
                base[energy_category_id]['subtotal_actual'] = Decimal(0.0)
274
                base[energy_category_id]['subtotal_saving'] = Decimal(0.0)
275
                base[energy_category_id]['subtotal_in_kgce_baseline'] = Decimal(0.0)
276
                base[energy_category_id]['subtotal_in_kgce_actual'] = Decimal(0.0)
277
                base[energy_category_id]['subtotal_in_kgce_saving'] = Decimal(0.0)
278
                base[energy_category_id]['subtotal_in_kgco2e_baseline'] = Decimal(0.0)
279
                base[energy_category_id]['subtotal_in_kgco2e_actual'] = Decimal(0.0)
280
                base[energy_category_id]['subtotal_in_kgco2e_saving'] = Decimal(0.0)
281
                # query base period's energy baseline
282
                cursor_energy_baseline.execute(" SELECT start_datetime_utc, actual_value "
283
                                               " FROM tbl_store_input_category_hourly "
284
                                               " WHERE store_id = %s "
285
                                               "     AND energy_category_id = %s "
286
                                               "     AND start_datetime_utc >= %s "
287
                                               "     AND start_datetime_utc < %s "
288
                                               " ORDER BY start_datetime_utc ",
289
                                               (store['id'],
290
                                                energy_category_id,
291
                                                base_start_datetime_utc,
292
                                                base_end_datetime_utc))
293
                rows_store_hourly = cursor_energy_baseline.fetchall()
294
295
                rows_store_periodically = utilities.aggregate_hourly_data_by_period(rows_store_hourly,
296
                                                                                    base_start_datetime_utc,
297
                                                                                    base_end_datetime_utc,
298
                                                                                    period_type)
299
                for row_store_periodically in rows_store_periodically:
300
                    current_datetime_local = row_store_periodically[0].replace(tzinfo=timezone.utc) + \
301
                                             timedelta(minutes=timezone_offset)
302
                    if period_type == 'hourly':
303
                        current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S')
304
                    elif period_type == 'daily':
305
                        current_datetime = current_datetime_local.strftime('%Y-%m-%d')
306
                    elif period_type == 'monthly':
307
                        current_datetime = current_datetime_local.strftime('%Y-%m')
308
                    elif period_type == 'yearly':
309
                        current_datetime = current_datetime_local.strftime('%Y')
310
311
                    baseline_value = Decimal(0.0) if row_store_periodically[1] is None else row_store_periodically[1]
312
                    base[energy_category_id]['timestamps'].append(current_datetime)
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313
                    base[energy_category_id]['values_baseline'].append(baseline_value)
314
                    base[energy_category_id]['subtotal_baseline'] += baseline_value
315
                    base[energy_category_id]['subtotal_in_kgce_baseline'] += baseline_value * kgce
316
                    base[energy_category_id]['subtotal_in_kgco2e_baseline'] += baseline_value * kgco2e
317
318
                # query base period's energy actual
319
                cursor_energy.execute(" SELECT start_datetime_utc, actual_value "
320
                                      " FROM tbl_store_input_category_hourly "
321
                                      " WHERE store_id = %s "
322
                                      "     AND energy_category_id = %s "
323
                                      "     AND start_datetime_utc >= %s "
324
                                      "     AND start_datetime_utc < %s "
325
                                      " ORDER BY start_datetime_utc ",
326
                                      (store['id'],
327
                                       energy_category_id,
328
                                       base_start_datetime_utc,
329
                                       base_end_datetime_utc))
330
                rows_store_hourly = cursor_energy.fetchall()
331
332
                rows_store_periodically = utilities.aggregate_hourly_data_by_period(rows_store_hourly,
333
                                                                                    base_start_datetime_utc,
334
                                                                                    base_end_datetime_utc,
335
                                                                                    period_type)
336
                for row_store_periodically in rows_store_periodically:
337
                    current_datetime_local = row_store_periodically[0].replace(tzinfo=timezone.utc) + \
338
                                             timedelta(minutes=timezone_offset)
339
                    if period_type == 'hourly':
340
                        current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S')
341
                    elif period_type == 'daily':
342
                        current_datetime = current_datetime_local.strftime('%Y-%m-%d')
343
                    elif period_type == 'monthly':
344
                        current_datetime = current_datetime_local.strftime('%Y-%m')
345
                    elif period_type == 'yearly':
346
                        current_datetime = current_datetime_local.strftime('%Y')
347
348
                    actual_value = Decimal(0.0) if row_store_periodically[1] is None else row_store_periodically[1]
349
                    base[energy_category_id]['values_actual'].append(actual_value)
350
                    base[energy_category_id]['subtotal_actual'] += actual_value
351
                    base[energy_category_id]['subtotal_in_kgce_actual'] += actual_value * kgce
352
                    base[energy_category_id]['subtotal_in_kgco2e_actual'] += actual_value * kgco2e
353
354
                # calculate base period's energy savings
355
                for i in range(len(base[energy_category_id]['values_baseline'])):
356
                    base[energy_category_id]['values_saving'].append(
357
                        base[energy_category_id]['values_baseline'][i] -
358
                        base[energy_category_id]['values_actual'][i])
359
360
                base[energy_category_id]['subtotal_saving'] = \
361
                    base[energy_category_id]['subtotal_baseline'] - \
362
                    base[energy_category_id]['subtotal_actual']
363
                base[energy_category_id]['subtotal_in_kgce_saving'] = \
364
                    base[energy_category_id]['subtotal_in_kgce_baseline'] - \
365
                    base[energy_category_id]['subtotal_in_kgce_actual']
366
                base[energy_category_id]['subtotal_in_kgco2e_saving'] = \
367
                    base[energy_category_id]['subtotal_in_kgco2e_baseline'] - \
368
                    base[energy_category_id]['subtotal_in_kgco2e_actual']
369
        ################################################################################################################
370
        # Step 7: query reporting period energy saving
371
        ################################################################################################################
372
        reporting = dict()
373
        if energy_category_set is not None and len(energy_category_set) > 0:
374
            for energy_category_id in energy_category_set:
375
                kgce = energy_category_dict[energy_category_id]['kgce']
376
                kgco2e = energy_category_dict[energy_category_id]['kgco2e']
377
378
                reporting[energy_category_id] = dict()
379
                reporting[energy_category_id]['timestamps'] = list()
380
                reporting[energy_category_id]['values_baseline'] = list()
381
                reporting[energy_category_id]['values_actual'] = list()
382
                reporting[energy_category_id]['values_saving'] = list()
383
                reporting[energy_category_id]['subtotal_baseline'] = Decimal(0.0)
384
                reporting[energy_category_id]['subtotal_actual'] = Decimal(0.0)
385
                reporting[energy_category_id]['subtotal_saving'] = Decimal(0.0)
386
                reporting[energy_category_id]['subtotal_in_kgce_baseline'] = Decimal(0.0)
387
                reporting[energy_category_id]['subtotal_in_kgce_actual'] = Decimal(0.0)
388
                reporting[energy_category_id]['subtotal_in_kgce_saving'] = Decimal(0.0)
389
                reporting[energy_category_id]['subtotal_in_kgco2e_baseline'] = Decimal(0.0)
390
                reporting[energy_category_id]['subtotal_in_kgco2e_actual'] = Decimal(0.0)
391
                reporting[energy_category_id]['subtotal_in_kgco2e_saving'] = Decimal(0.0)
392
                # query reporting period's energy baseline
393
                cursor_energy_baseline.execute(" SELECT start_datetime_utc, actual_value "
394
                                               " FROM tbl_store_input_category_hourly "
395
                                               " WHERE store_id = %s "
396
                                               "     AND energy_category_id = %s "
397
                                               "     AND start_datetime_utc >= %s "
398
                                               "     AND start_datetime_utc < %s "
399
                                               " ORDER BY start_datetime_utc ",
400
                                               (store['id'],
401
                                                energy_category_id,
402
                                                reporting_start_datetime_utc,
403
                                                reporting_end_datetime_utc))
404
                rows_store_hourly = cursor_energy_baseline.fetchall()
405
406
                rows_store_periodically = utilities.aggregate_hourly_data_by_period(rows_store_hourly,
407
                                                                                    reporting_start_datetime_utc,
408
                                                                                    reporting_end_datetime_utc,
409
                                                                                    period_type)
410
                for row_store_periodically in rows_store_periodically:
411
                    current_datetime_local = row_store_periodically[0].replace(tzinfo=timezone.utc) + \
412
                                             timedelta(minutes=timezone_offset)
413
                    if period_type == 'hourly':
414
                        current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S')
415
                    elif period_type == 'daily':
416
                        current_datetime = current_datetime_local.strftime('%Y-%m-%d')
417
                    elif period_type == 'monthly':
418
                        current_datetime = current_datetime_local.strftime('%Y-%m')
419
                    elif period_type == 'yearly':
420
                        current_datetime = current_datetime_local.strftime('%Y')
421
422
                    baseline_value = Decimal(0.0) if row_store_periodically[1] is None else row_store_periodically[1]
423
                    reporting[energy_category_id]['timestamps'].append(current_datetime)
424
                    reporting[energy_category_id]['values_baseline'].append(baseline_value)
425
                    reporting[energy_category_id]['subtotal_baseline'] += baseline_value
426
                    reporting[energy_category_id]['subtotal_in_kgce_baseline'] += baseline_value * kgce
427
                    reporting[energy_category_id]['subtotal_in_kgco2e_baseline'] += baseline_value * kgco2e
428
429
                # query reporting period's energy actual
430
                cursor_energy.execute(" SELECT start_datetime_utc, actual_value "
431
                                      " FROM tbl_store_input_category_hourly "
432
                                      " WHERE store_id = %s "
433
                                      "     AND energy_category_id = %s "
434
                                      "     AND start_datetime_utc >= %s "
435
                                      "     AND start_datetime_utc < %s "
436
                                      " ORDER BY start_datetime_utc ",
437
                                      (store['id'],
438
                                       energy_category_id,
439
                                       reporting_start_datetime_utc,
440
                                       reporting_end_datetime_utc))
441
                rows_store_hourly = cursor_energy.fetchall()
442
443
                rows_store_periodically = utilities.aggregate_hourly_data_by_period(rows_store_hourly,
444
                                                                                    reporting_start_datetime_utc,
445
                                                                                    reporting_end_datetime_utc,
446
                                                                                    period_type)
447
                for row_store_periodically in rows_store_periodically:
448
                    current_datetime_local = row_store_periodically[0].replace(tzinfo=timezone.utc) + \
449
                                             timedelta(minutes=timezone_offset)
450
                    if period_type == 'hourly':
451
                        current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S')
452
                    elif period_type == 'daily':
453
                        current_datetime = current_datetime_local.strftime('%Y-%m-%d')
454
                    elif period_type == 'monthly':
455
                        current_datetime = current_datetime_local.strftime('%Y-%m')
456
                    elif period_type == 'yearly':
457
                        current_datetime = current_datetime_local.strftime('%Y')
458
459
                    actual_value = Decimal(0.0) if row_store_periodically[1] is None else row_store_periodically[1]
460
                    reporting[energy_category_id]['values_actual'].append(actual_value)
461
                    reporting[energy_category_id]['subtotal_actual'] += actual_value
462
                    reporting[energy_category_id]['subtotal_in_kgce_actual'] += actual_value * kgce
463
                    reporting[energy_category_id]['subtotal_in_kgco2e_actual'] += actual_value * kgco2e
464
465
                # calculate reporting period's energy savings
466
                for i in range(len(reporting[energy_category_id]['values_baseline'])):
467
                    reporting[energy_category_id]['values_saving'].append(
468
                        reporting[energy_category_id]['values_baseline'][i] -
469
                        reporting[energy_category_id]['values_actual'][i])
470
471
                reporting[energy_category_id]['subtotal_saving'] = \
472
                    reporting[energy_category_id]['subtotal_baseline'] - \
473
                    reporting[energy_category_id]['subtotal_actual']
474
                reporting[energy_category_id]['subtotal_in_kgce_saving'] = \
475
                    reporting[energy_category_id]['subtotal_in_kgce_baseline'] - \
476
                    reporting[energy_category_id]['subtotal_in_kgce_actual']
477
                reporting[energy_category_id]['subtotal_in_kgco2e_saving'] = \
478
                    reporting[energy_category_id]['subtotal_in_kgco2e_baseline'] - \
479
                    reporting[energy_category_id]['subtotal_in_kgco2e_actual']
480
        ################################################################################################################
481
        # Step 8: query tariff data
482
        ################################################################################################################
483
        parameters_data = dict()
484
        parameters_data['names'] = list()
485
        parameters_data['timestamps'] = list()
486
        parameters_data['values'] = list()
487
        if energy_category_set is not None and len(energy_category_set) > 0:
488
            for energy_category_id in energy_category_set:
489
                energy_category_tariff_dict = utilities.get_energy_category_tariffs(store['cost_center_id'],
490
                                                                                    energy_category_id,
491
                                                                                    reporting_start_datetime_utc,
492
                                                                                    reporting_end_datetime_utc)
493
                tariff_timestamp_list = list()
494
                tariff_value_list = list()
495
                for k, v in energy_category_tariff_dict.items():
496
                    # convert k from utc to local
497
                    k = k + timedelta(minutes=timezone_offset)
498
                    tariff_timestamp_list.append(k.isoformat()[0:19][0:19])
499
                    tariff_value_list.append(v)
500
501
                parameters_data['names'].append('TARIFF-' + energy_category_dict[energy_category_id]['name'])
502
                parameters_data['timestamps'].append(tariff_timestamp_list)
503
                parameters_data['values'].append(tariff_value_list)
504
505
        ################################################################################################################
506
        # Step 9: query associated sensors and points data
507
        ################################################################################################################
508
        for point in point_list:
509
            point_values = []
510
            point_timestamps = []
511
            if point['object_type'] == 'ANALOG_VALUE':
512
                query = (" SELECT utc_date_time, actual_value "
513
                         " FROM tbl_analog_value "
514
                         " WHERE point_id = %s "
515
                         "       AND utc_date_time BETWEEN %s AND %s "
516
                         " ORDER BY utc_date_time ")
517
                cursor_historical.execute(query, (point['id'],
518
                                                  reporting_start_datetime_utc,
519
                                                  reporting_end_datetime_utc))
520
                rows = cursor_historical.fetchall()
521
522
                if rows is not None and len(rows) > 0:
523
                    for row in rows:
524
                        current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \
525
                                                 timedelta(minutes=timezone_offset)
526
                        current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S')
527
                        point_timestamps.append(current_datetime)
528
                        point_values.append(row[1])
529
530
            elif point['object_type'] == 'ENERGY_VALUE':
531
                query = (" SELECT utc_date_time, actual_value "
532
                         " FROM tbl_energy_value "
533
                         " WHERE point_id = %s "
534
                         "       AND utc_date_time BETWEEN %s AND %s "
535
                         " ORDER BY utc_date_time ")
536
                cursor_historical.execute(query, (point['id'],
537
                                                  reporting_start_datetime_utc,
538
                                                  reporting_end_datetime_utc))
539
                rows = cursor_historical.fetchall()
540
541
                if rows is not None and len(rows) > 0:
542
                    for row in rows:
543
                        current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \
544
                                                 timedelta(minutes=timezone_offset)
545
                        current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S')
546
                        point_timestamps.append(current_datetime)
547
                        point_values.append(row[1])
548
            elif point['object_type'] == 'DIGITAL_VALUE':
549
                query = (" SELECT utc_date_time, actual_value "
550
                         " FROM tbl_digital_value "
551
                         " WHERE point_id = %s "
552
                         "       AND utc_date_time BETWEEN %s AND %s ")
553
                cursor_historical.execute(query, (point['id'],
554
                                                  reporting_start_datetime_utc,
555
                                                  reporting_end_datetime_utc))
556
                rows = cursor_historical.fetchall()
557
558
                if rows is not None and len(rows) > 0:
559
                    for row in rows:
560
                        current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \
561
                                                 timedelta(minutes=timezone_offset)
562
                        current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S')
563
                        point_timestamps.append(current_datetime)
564
                        point_values.append(row[1])
565
566
            parameters_data['names'].append(point['name'] + ' (' + point['units'] + ')')
567
            parameters_data['timestamps'].append(point_timestamps)
568
            parameters_data['values'].append(point_values)
569
570
        ################################################################################################################
571
        # Step 10: construct the report
572
        ################################################################################################################
573
        if cursor_system:
574
            cursor_system.close()
575
        if cnx_system:
576
            cnx_system.disconnect()
577
578
        if cursor_energy:
579
            cursor_energy.close()
580
        if cnx_energy:
581
            cnx_energy.disconnect()
582
583
        if cursor_energy_baseline:
584
            cursor_energy_baseline.close()
585
        if cnx_energy_baseline:
586
            cnx_energy_baseline.disconnect()
587
588
        result = dict()
589
590
        result['store'] = dict()
591
        result['store']['name'] = store['name']
592
        result['store']['area'] = store['area']
593
594
        result['base_period'] = dict()
595
        result['base_period']['names'] = list()
596
        result['base_period']['units'] = list()
597
        result['base_period']['timestamps'] = list()
598
        result['base_period']['values_saving'] = list()
599
        result['base_period']['subtotals_saving'] = list()
600
        result['base_period']['subtotals_in_kgce_saving'] = list()
601
        result['base_period']['subtotals_in_kgco2e_saving'] = list()
602
        result['base_period']['total_in_kgce_saving'] = Decimal(0.0)
603
        result['base_period']['total_in_kgco2e_saving'] = Decimal(0.0)
604
        if energy_category_set is not None and len(energy_category_set) > 0:
605
            for energy_category_id in energy_category_set:
606
                result['base_period']['names'].append(energy_category_dict[energy_category_id]['name'])
607
                result['base_period']['units'].append(energy_category_dict[energy_category_id]['unit_of_measure'])
608
                result['base_period']['timestamps'].append(base[energy_category_id]['timestamps'])
609
                result['base_period']['values_saving'].append(base[energy_category_id]['values_saving'])
610
                result['base_period']['subtotals_saving'].append(base[energy_category_id]['subtotal_saving'])
611
                result['base_period']['subtotals_in_kgce_saving'].append(
612
                    base[energy_category_id]['subtotal_in_kgce_saving'])
613
                result['base_period']['subtotals_in_kgco2e_saving'].append(
614
                    base[energy_category_id]['subtotal_in_kgco2e_saving'])
615
                result['base_period']['total_in_kgce_saving'] += base[energy_category_id]['subtotal_in_kgce_saving']
616
                result['base_period']['total_in_kgco2e_saving'] += base[energy_category_id]['subtotal_in_kgco2e_saving']
617
618
        result['reporting_period'] = dict()
619
        result['reporting_period']['names'] = list()
620
        result['reporting_period']['energy_category_ids'] = list()
621
        result['reporting_period']['units'] = list()
622
        result['reporting_period']['timestamps'] = list()
623
        result['reporting_period']['values_saving'] = list()
624
        result['reporting_period']['subtotals_saving'] = list()
625
        result['reporting_period']['subtotals_in_kgce_saving'] = list()
626
        result['reporting_period']['subtotals_in_kgco2e_saving'] = list()
627
        result['reporting_period']['subtotals_per_unit_area_saving'] = list()
628
        result['reporting_period']['increment_rates_saving'] = list()
629
        result['reporting_period']['total_in_kgce_saving'] = Decimal(0.0)
630
        result['reporting_period']['total_in_kgco2e_saving'] = Decimal(0.0)
631
        result['reporting_period']['increment_rate_in_kgce_saving'] = Decimal(0.0)
632
        result['reporting_period']['increment_rate_in_kgco2e_saving'] = Decimal(0.0)
633
634
        if energy_category_set is not None and len(energy_category_set) > 0:
635
            for energy_category_id in energy_category_set:
636
                result['reporting_period']['names'].append(energy_category_dict[energy_category_id]['name'])
637
                result['reporting_period']['energy_category_ids'].append(energy_category_id)
638
                result['reporting_period']['units'].append(energy_category_dict[energy_category_id]['unit_of_measure'])
639
                result['reporting_period']['timestamps'].append(reporting[energy_category_id]['timestamps'])
640
                result['reporting_period']['values_saving'].append(reporting[energy_category_id]['values_saving'])
641
                result['reporting_period']['subtotals_saving'].append(reporting[energy_category_id]['subtotal_saving'])
642
                result['reporting_period']['subtotals_in_kgce_saving'].append(
643
                    reporting[energy_category_id]['subtotal_in_kgce_saving'])
644
                result['reporting_period']['subtotals_in_kgco2e_saving'].append(
645
                    reporting[energy_category_id]['subtotal_in_kgco2e_saving'])
646
                result['reporting_period']['subtotals_per_unit_area_saving'].append(
647
                    reporting[energy_category_id]['subtotal_saving'] / store['area'] if store['area'] > 0.0 else None)
648
                result['reporting_period']['increment_rates_saving'].append(
649
                    (reporting[energy_category_id]['subtotal_saving'] - base[energy_category_id]['subtotal_saving']) /
650
                    base[energy_category_id]['subtotal_saving']
651
                    if base[energy_category_id]['subtotal_saving'] > 0.0 else None)
652
                result['reporting_period']['total_in_kgce_saving'] += \
653
                    reporting[energy_category_id]['subtotal_in_kgce_saving']
654
                result['reporting_period']['total_in_kgco2e_saving'] += \
655
                    reporting[energy_category_id]['subtotal_in_kgco2e_saving']
656
657
        result['reporting_period']['total_in_kgco2e_per_unit_area_saving'] = \
658
            result['reporting_period']['total_in_kgce_saving'] / store['area'] if store['area'] > 0.0 else None
659
660
        result['reporting_period']['increment_rate_in_kgce_saving'] = \
661
            (result['reporting_period']['total_in_kgce_saving'] - result['base_period']['total_in_kgce_saving']) / \
662
            result['base_period']['total_in_kgce_saving'] \
663
            if result['base_period']['total_in_kgce_saving'] > Decimal(0.0) else None
664
665
        result['reporting_period']['total_in_kgce_per_unit_area_saving'] = \
666
            result['reporting_period']['total_in_kgco2e_saving'] / store['area'] if store['area'] > 0.0 else None
667
668
        result['reporting_period']['increment_rate_in_kgco2e_saving'] = \
669
            (result['reporting_period']['total_in_kgco2e_saving'] - result['base_period']['total_in_kgco2e_saving']) / \
670
            result['base_period']['total_in_kgco2e_saving'] \
671
            if result['base_period']['total_in_kgco2e_saving'] > Decimal(0.0) else None
672
673
        result['parameters'] = {
674
            "names": parameters_data['names'],
675
            "timestamps": parameters_data['timestamps'],
676
            "values": parameters_data['values']
677
        }
678
679
        resp.body = json.dumps(result)
680