@@ 10-685 (lines=676) @@ | ||
7 | from decimal import Decimal |
|
8 | ||
9 | ||
10 | class Reporting: |
|
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 shopfloor |
|
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 | shopfloor_id = req.params.get('shopfloorid') |
|
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 shopfloor_id is None: |
|
46 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_SHOPFLOOR_ID') |
|
47 | else: |
|
48 | shopfloor_id = str.strip(shopfloor_id) |
|
49 | if not shopfloor_id.isdigit() or int(shopfloor_id) <= 0: |
|
50 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_SHOPFLOOR_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_START_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_END_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_END_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_START_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_START_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_END_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_END_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_END_DATETIME') |
|
119 | ||
120 | ################################################################################################################ |
|
121 | # Step 2: query the shopfloor |
|
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_shopfloors " |
|
137 | " WHERE id = %s ", (shopfloor_id,)) |
|
138 | row_shopfloor = cursor_system.fetchone() |
|
139 | if row_shopfloor 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.SHOPFLOOR_NOT_FOUND') |
|
160 | ||
161 | shopfloor = dict() |
|
162 | shopfloor['id'] = row_shopfloor[0] |
|
163 | shopfloor['name'] = row_shopfloor[1] |
|
164 | shopfloor['area'] = row_shopfloor[2] |
|
165 | shopfloor['cost_center_id'] = row_shopfloor[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_shopfloor_input_category_hourly " |
|
174 | " WHERE shopfloor_id = %s " |
|
175 | " AND start_datetime_utc >= %s " |
|
176 | " AND start_datetime_utc < %s ", |
|
177 | (shopfloor['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_shopfloor_input_category_hourly " |
|
186 | " WHERE shopfloor_id = %s " |
|
187 | " AND start_datetime_utc >= %s " |
|
188 | " AND start_datetime_utc < %s ", |
|
189 | (shopfloor['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_shopfloors st, tbl_sensors se, tbl_shopfloors_sensors ss, " |
|
237 | " tbl_points p, tbl_sensors_points sp " |
|
238 | " WHERE st.id = %s AND st.id = ss.shopfloor_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 ", (shopfloor['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_shopfloors s, tbl_shopfloors_points sp, tbl_points p " |
|
251 | " WHERE s.id = %s AND s.id = sp.shopfloor_id AND sp.point_id = p.id " |
|
252 | " ORDER BY p.id ", (shopfloor['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_shopfloor_input_category_hourly " |
|
284 | " WHERE shopfloor_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 | (shopfloor['id'], |
|
290 | energy_category_id, |
|
291 | base_start_datetime_utc, |
|
292 | base_end_datetime_utc)) |
|
293 | rows_shopfloor_hourly = cursor_energy_baseline.fetchall() |
|
294 | ||
295 | rows_shopfloor_periodically = utilities.aggregate_hourly_data_by_period(rows_shopfloor_hourly, |
|
296 | base_start_datetime_utc, |
|
297 | base_end_datetime_utc, |
|
298 | period_type) |
|
299 | for row_shopfloor_periodically in rows_shopfloor_periodically: |
|
300 | current_datetime_local = row_shopfloor_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_shopfloor_periodically[1] is None \ |
|
312 | else row_shopfloor_periodically[1] |
|
313 | base[energy_category_id]['timestamps'].append(current_datetime) |
|
314 | base[energy_category_id]['values_baseline'].append(baseline_value) |
|
315 | base[energy_category_id]['subtotal_baseline'] += baseline_value |
|
316 | base[energy_category_id]['subtotal_in_kgce_baseline'] += baseline_value * kgce |
|
317 | base[energy_category_id]['subtotal_in_kgco2e_baseline'] += baseline_value * kgco2e |
|
318 | ||
319 | # query base period's energy actual |
|
320 | cursor_energy.execute(" SELECT start_datetime_utc, actual_value " |
|
321 | " FROM tbl_shopfloor_input_category_hourly " |
|
322 | " WHERE shopfloor_id = %s " |
|
323 | " AND energy_category_id = %s " |
|
324 | " AND start_datetime_utc >= %s " |
|
325 | " AND start_datetime_utc < %s " |
|
326 | " ORDER BY start_datetime_utc ", |
|
327 | (shopfloor['id'], |
|
328 | energy_category_id, |
|
329 | base_start_datetime_utc, |
|
330 | base_end_datetime_utc)) |
|
331 | rows_shopfloor_hourly = cursor_energy.fetchall() |
|
332 | ||
333 | rows_shopfloor_periodically = utilities.aggregate_hourly_data_by_period(rows_shopfloor_hourly, |
|
334 | base_start_datetime_utc, |
|
335 | base_end_datetime_utc, |
|
336 | period_type) |
|
337 | for row_shopfloor_periodically in rows_shopfloor_periodically: |
|
338 | current_datetime_local = row_shopfloor_periodically[0].replace(tzinfo=timezone.utc) + \ |
|
339 | timedelta(minutes=timezone_offset) |
|
340 | if period_type == 'hourly': |
|
341 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
|
342 | elif period_type == 'daily': |
|
343 | current_datetime = current_datetime_local.strftime('%Y-%m-%d') |
|
344 | elif period_type == 'monthly': |
|
345 | current_datetime = current_datetime_local.strftime('%Y-%m') |
|
346 | elif period_type == 'yearly': |
|
347 | current_datetime = current_datetime_local.strftime('%Y') |
|
348 | ||
349 | actual_value = Decimal(0.0) if row_shopfloor_periodically[1] is None \ |
|
350 | else row_shopfloor_periodically[1] |
|
351 | base[energy_category_id]['values_actual'].append(actual_value) |
|
352 | base[energy_category_id]['subtotal_actual'] += actual_value |
|
353 | base[energy_category_id]['subtotal_in_kgce_actual'] += actual_value * kgce |
|
354 | base[energy_category_id]['subtotal_in_kgco2e_actual'] += actual_value * kgco2e |
|
355 | ||
356 | # calculate base period's energy savings |
|
357 | for i in range(len(base[energy_category_id]['values_baseline'])): |
|
358 | base[energy_category_id]['values_saving'].append( |
|
359 | base[energy_category_id]['values_baseline'][i] - |
|
360 | base[energy_category_id]['values_actual'][i]) |
|
361 | ||
362 | base[energy_category_id]['subtotal_saving'] = \ |
|
363 | base[energy_category_id]['subtotal_baseline'] - \ |
|
364 | base[energy_category_id]['subtotal_actual'] |
|
365 | base[energy_category_id]['subtotal_in_kgce_saving'] = \ |
|
366 | base[energy_category_id]['subtotal_in_kgce_baseline'] - \ |
|
367 | base[energy_category_id]['subtotal_in_kgce_actual'] |
|
368 | base[energy_category_id]['subtotal_in_kgco2e_saving'] = \ |
|
369 | base[energy_category_id]['subtotal_in_kgco2e_baseline'] - \ |
|
370 | base[energy_category_id]['subtotal_in_kgco2e_actual'] |
|
371 | ################################################################################################################ |
|
372 | # Step 7: query reporting period energy saving |
|
373 | ################################################################################################################ |
|
374 | reporting = dict() |
|
375 | if energy_category_set is not None and len(energy_category_set) > 0: |
|
376 | for energy_category_id in energy_category_set: |
|
377 | kgce = energy_category_dict[energy_category_id]['kgce'] |
|
378 | kgco2e = energy_category_dict[energy_category_id]['kgco2e'] |
|
379 | ||
380 | reporting[energy_category_id] = dict() |
|
381 | reporting[energy_category_id]['timestamps'] = list() |
|
382 | reporting[energy_category_id]['values_baseline'] = list() |
|
383 | reporting[energy_category_id]['values_actual'] = list() |
|
384 | reporting[energy_category_id]['values_saving'] = list() |
|
385 | reporting[energy_category_id]['subtotal_baseline'] = Decimal(0.0) |
|
386 | reporting[energy_category_id]['subtotal_actual'] = Decimal(0.0) |
|
387 | reporting[energy_category_id]['subtotal_saving'] = Decimal(0.0) |
|
388 | reporting[energy_category_id]['subtotal_in_kgce_baseline'] = Decimal(0.0) |
|
389 | reporting[energy_category_id]['subtotal_in_kgce_actual'] = Decimal(0.0) |
|
390 | reporting[energy_category_id]['subtotal_in_kgce_saving'] = Decimal(0.0) |
|
391 | reporting[energy_category_id]['subtotal_in_kgco2e_baseline'] = Decimal(0.0) |
|
392 | reporting[energy_category_id]['subtotal_in_kgco2e_actual'] = Decimal(0.0) |
|
393 | reporting[energy_category_id]['subtotal_in_kgco2e_saving'] = Decimal(0.0) |
|
394 | # query reporting period's energy baseline |
|
395 | cursor_energy_baseline.execute(" SELECT start_datetime_utc, actual_value " |
|
396 | " FROM tbl_shopfloor_input_category_hourly " |
|
397 | " WHERE shopfloor_id = %s " |
|
398 | " AND energy_category_id = %s " |
|
399 | " AND start_datetime_utc >= %s " |
|
400 | " AND start_datetime_utc < %s " |
|
401 | " ORDER BY start_datetime_utc ", |
|
402 | (shopfloor['id'], |
|
403 | energy_category_id, |
|
404 | reporting_start_datetime_utc, |
|
405 | reporting_end_datetime_utc)) |
|
406 | rows_shopfloor_hourly = cursor_energy_baseline.fetchall() |
|
407 | ||
408 | rows_shopfloor_periodically = utilities.aggregate_hourly_data_by_period(rows_shopfloor_hourly, |
|
409 | reporting_start_datetime_utc, |
|
410 | reporting_end_datetime_utc, |
|
411 | period_type) |
|
412 | for row_shopfloor_periodically in rows_shopfloor_periodically: |
|
413 | current_datetime_local = row_shopfloor_periodically[0].replace(tzinfo=timezone.utc) + \ |
|
414 | timedelta(minutes=timezone_offset) |
|
415 | if period_type == 'hourly': |
|
416 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
|
417 | elif period_type == 'daily': |
|
418 | current_datetime = current_datetime_local.strftime('%Y-%m-%d') |
|
419 | elif period_type == 'monthly': |
|
420 | current_datetime = current_datetime_local.strftime('%Y-%m') |
|
421 | elif period_type == 'yearly': |
|
422 | current_datetime = current_datetime_local.strftime('%Y') |
|
423 | ||
424 | baseline_value = Decimal(0.0) if row_shopfloor_periodically[1] is None \ |
|
425 | else row_shopfloor_periodically[1] |
|
426 | reporting[energy_category_id]['timestamps'].append(current_datetime) |
|
427 | reporting[energy_category_id]['values_baseline'].append(baseline_value) |
|
428 | reporting[energy_category_id]['subtotal_baseline'] += baseline_value |
|
429 | reporting[energy_category_id]['subtotal_in_kgce_baseline'] += baseline_value * kgce |
|
430 | reporting[energy_category_id]['subtotal_in_kgco2e_baseline'] += baseline_value * kgco2e |
|
431 | ||
432 | # query reporting period's energy actual |
|
433 | cursor_energy.execute(" SELECT start_datetime_utc, actual_value " |
|
434 | " FROM tbl_shopfloor_input_category_hourly " |
|
435 | " WHERE shopfloor_id = %s " |
|
436 | " AND energy_category_id = %s " |
|
437 | " AND start_datetime_utc >= %s " |
|
438 | " AND start_datetime_utc < %s " |
|
439 | " ORDER BY start_datetime_utc ", |
|
440 | (shopfloor['id'], |
|
441 | energy_category_id, |
|
442 | reporting_start_datetime_utc, |
|
443 | reporting_end_datetime_utc)) |
|
444 | rows_shopfloor_hourly = cursor_energy.fetchall() |
|
445 | ||
446 | rows_shopfloor_periodically = utilities.aggregate_hourly_data_by_period(rows_shopfloor_hourly, |
|
447 | reporting_start_datetime_utc, |
|
448 | reporting_end_datetime_utc, |
|
449 | period_type) |
|
450 | for row_shopfloor_periodically in rows_shopfloor_periodically: |
|
451 | current_datetime_local = row_shopfloor_periodically[0].replace(tzinfo=timezone.utc) + \ |
|
452 | timedelta(minutes=timezone_offset) |
|
453 | if period_type == 'hourly': |
|
454 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
|
455 | elif period_type == 'daily': |
|
456 | current_datetime = current_datetime_local.strftime('%Y-%m-%d') |
|
457 | elif period_type == 'monthly': |
|
458 | current_datetime = current_datetime_local.strftime('%Y-%m') |
|
459 | elif period_type == 'yearly': |
|
460 | current_datetime = current_datetime_local.strftime('%Y') |
|
461 | ||
462 | actual_value = Decimal(0.0) if row_shopfloor_periodically[1] is None \ |
|
463 | else row_shopfloor_periodically[1] |
|
464 | reporting[energy_category_id]['values_actual'].append(actual_value) |
|
465 | reporting[energy_category_id]['subtotal_actual'] += actual_value |
|
466 | reporting[energy_category_id]['subtotal_in_kgce_actual'] += actual_value * kgce |
|
467 | reporting[energy_category_id]['subtotal_in_kgco2e_actual'] += actual_value * kgco2e |
|
468 | ||
469 | # calculate reporting period's energy savings |
|
470 | for i in range(len(reporting[energy_category_id]['values_baseline'])): |
|
471 | reporting[energy_category_id]['values_saving'].append( |
|
472 | reporting[energy_category_id]['values_baseline'][i] - |
|
473 | reporting[energy_category_id]['values_actual'][i]) |
|
474 | ||
475 | reporting[energy_category_id]['subtotal_saving'] = \ |
|
476 | reporting[energy_category_id]['subtotal_baseline'] - \ |
|
477 | reporting[energy_category_id]['subtotal_actual'] |
|
478 | reporting[energy_category_id]['subtotal_in_kgce_saving'] = \ |
|
479 | reporting[energy_category_id]['subtotal_in_kgce_baseline'] - \ |
|
480 | reporting[energy_category_id]['subtotal_in_kgce_actual'] |
|
481 | reporting[energy_category_id]['subtotal_in_kgco2e_saving'] = \ |
|
482 | reporting[energy_category_id]['subtotal_in_kgco2e_baseline'] - \ |
|
483 | reporting[energy_category_id]['subtotal_in_kgco2e_actual'] |
|
484 | ################################################################################################################ |
|
485 | # Step 8: query tariff data |
|
486 | ################################################################################################################ |
|
487 | parameters_data = dict() |
|
488 | parameters_data['names'] = list() |
|
489 | parameters_data['timestamps'] = list() |
|
490 | parameters_data['values'] = list() |
|
491 | if energy_category_set is not None and len(energy_category_set) > 0: |
|
492 | for energy_category_id in energy_category_set: |
|
493 | energy_category_tariff_dict = utilities.get_energy_category_tariffs(shopfloor['cost_center_id'], |
|
494 | energy_category_id, |
|
495 | reporting_start_datetime_utc, |
|
496 | reporting_end_datetime_utc) |
|
497 | tariff_timestamp_list = list() |
|
498 | tariff_value_list = list() |
|
499 | for k, v in energy_category_tariff_dict.items(): |
|
500 | # convert k from utc to local |
|
501 | k = k + timedelta(minutes=timezone_offset) |
|
502 | tariff_timestamp_list.append(k.isoformat()[0:19][0:19]) |
|
503 | tariff_value_list.append(v) |
|
504 | ||
505 | parameters_data['names'].append('TARIFF-' + energy_category_dict[energy_category_id]['name']) |
|
506 | parameters_data['timestamps'].append(tariff_timestamp_list) |
|
507 | parameters_data['values'].append(tariff_value_list) |
|
508 | ||
509 | ################################################################################################################ |
|
510 | # Step 9: query associated sensors and points data |
|
511 | ################################################################################################################ |
|
512 | for point in point_list: |
|
513 | point_values = [] |
|
514 | point_timestamps = [] |
|
515 | if point['object_type'] == 'ANALOG_VALUE': |
|
516 | query = (" SELECT utc_date_time, actual_value " |
|
517 | " FROM tbl_analog_value " |
|
518 | " WHERE point_id = %s " |
|
519 | " AND utc_date_time BETWEEN %s AND %s " |
|
520 | " ORDER BY utc_date_time ") |
|
521 | cursor_historical.execute(query, (point['id'], |
|
522 | reporting_start_datetime_utc, |
|
523 | reporting_end_datetime_utc)) |
|
524 | rows = cursor_historical.fetchall() |
|
525 | ||
526 | if rows is not None and len(rows) > 0: |
|
527 | for row in rows: |
|
528 | current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ |
|
529 | timedelta(minutes=timezone_offset) |
|
530 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
|
531 | point_timestamps.append(current_datetime) |
|
532 | point_values.append(row[1]) |
|
533 | ||
534 | elif point['object_type'] == 'ENERGY_VALUE': |
|
535 | query = (" SELECT utc_date_time, actual_value " |
|
536 | " FROM tbl_energy_value " |
|
537 | " WHERE point_id = %s " |
|
538 | " AND utc_date_time BETWEEN %s AND %s " |
|
539 | " ORDER BY utc_date_time ") |
|
540 | cursor_historical.execute(query, (point['id'], |
|
541 | reporting_start_datetime_utc, |
|
542 | reporting_end_datetime_utc)) |
|
543 | rows = cursor_historical.fetchall() |
|
544 | ||
545 | if rows is not None and len(rows) > 0: |
|
546 | for row in rows: |
|
547 | current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ |
|
548 | timedelta(minutes=timezone_offset) |
|
549 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
|
550 | point_timestamps.append(current_datetime) |
|
551 | point_values.append(row[1]) |
|
552 | elif point['object_type'] == 'DIGITAL_VALUE': |
|
553 | query = (" SELECT utc_date_time, actual_value " |
|
554 | " FROM tbl_digital_value " |
|
555 | " WHERE point_id = %s " |
|
556 | " AND utc_date_time BETWEEN %s AND %s ") |
|
557 | cursor_historical.execute(query, (point['id'], |
|
558 | reporting_start_datetime_utc, |
|
559 | reporting_end_datetime_utc)) |
|
560 | rows = cursor_historical.fetchall() |
|
561 | ||
562 | if rows is not None and len(rows) > 0: |
|
563 | for row in rows: |
|
564 | current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ |
|
565 | timedelta(minutes=timezone_offset) |
|
566 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
|
567 | point_timestamps.append(current_datetime) |
|
568 | point_values.append(row[1]) |
|
569 | ||
570 | parameters_data['names'].append(point['name'] + ' (' + point['units'] + ')') |
|
571 | parameters_data['timestamps'].append(point_timestamps) |
|
572 | parameters_data['values'].append(point_values) |
|
573 | ||
574 | ################################################################################################################ |
|
575 | # Step 10: construct the report |
|
576 | ################################################################################################################ |
|
577 | if cursor_system: |
|
578 | cursor_system.close() |
|
579 | if cnx_system: |
|
580 | cnx_system.disconnect() |
|
581 | ||
582 | if cursor_energy: |
|
583 | cursor_energy.close() |
|
584 | if cnx_energy: |
|
585 | cnx_energy.disconnect() |
|
586 | ||
587 | if cursor_energy_baseline: |
|
588 | cursor_energy_baseline.close() |
|
589 | if cnx_energy_baseline: |
|
590 | cnx_energy_baseline.disconnect() |
|
591 | ||
592 | result = dict() |
|
593 | ||
594 | result['shopfloor'] = dict() |
|
595 | result['shopfloor']['name'] = shopfloor['name'] |
|
596 | result['shopfloor']['area'] = shopfloor['area'] |
|
597 | ||
598 | result['base_period'] = dict() |
|
599 | result['base_period']['names'] = list() |
|
600 | result['base_period']['units'] = list() |
|
601 | result['base_period']['timestamps'] = list() |
|
602 | result['base_period']['values_saving'] = list() |
|
603 | result['base_period']['subtotals_saving'] = list() |
|
604 | result['base_period']['subtotals_in_kgce_saving'] = list() |
|
605 | result['base_period']['subtotals_in_kgco2e_saving'] = list() |
|
606 | result['base_period']['total_in_kgce_saving'] = Decimal(0.0) |
|
607 | result['base_period']['total_in_kgco2e_saving'] = Decimal(0.0) |
|
608 | if energy_category_set is not None and len(energy_category_set) > 0: |
|
609 | for energy_category_id in energy_category_set: |
|
610 | result['base_period']['names'].append(energy_category_dict[energy_category_id]['name']) |
|
611 | result['base_period']['units'].append(energy_category_dict[energy_category_id]['unit_of_measure']) |
|
612 | result['base_period']['timestamps'].append(base[energy_category_id]['timestamps']) |
|
613 | result['base_period']['values_saving'].append(base[energy_category_id]['values_saving']) |
|
614 | result['base_period']['subtotals_saving'].append(base[energy_category_id]['subtotal_saving']) |
|
615 | result['base_period']['subtotals_in_kgce_saving'].append( |
|
616 | base[energy_category_id]['subtotal_in_kgce_saving']) |
|
617 | result['base_period']['subtotals_in_kgco2e_saving'].append( |
|
618 | base[energy_category_id]['subtotal_in_kgco2e_saving']) |
|
619 | result['base_period']['total_in_kgce_saving'] += base[energy_category_id]['subtotal_in_kgce_saving'] |
|
620 | result['base_period']['total_in_kgco2e_saving'] += base[energy_category_id]['subtotal_in_kgco2e_saving'] |
|
621 | ||
622 | result['reporting_period'] = dict() |
|
623 | result['reporting_period']['names'] = list() |
|
624 | result['reporting_period']['energy_category_ids'] = list() |
|
625 | result['reporting_period']['units'] = list() |
|
626 | result['reporting_period']['timestamps'] = list() |
|
627 | result['reporting_period']['values_saving'] = list() |
|
628 | result['reporting_period']['subtotals_saving'] = list() |
|
629 | result['reporting_period']['subtotals_in_kgce_saving'] = list() |
|
630 | result['reporting_period']['subtotals_in_kgco2e_saving'] = list() |
|
631 | result['reporting_period']['subtotals_per_unit_area_saving'] = list() |
|
632 | result['reporting_period']['increment_rates_saving'] = list() |
|
633 | result['reporting_period']['total_in_kgce_saving'] = Decimal(0.0) |
|
634 | result['reporting_period']['total_in_kgco2e_saving'] = Decimal(0.0) |
|
635 | result['reporting_period']['increment_rate_in_kgce_saving'] = Decimal(0.0) |
|
636 | result['reporting_period']['increment_rate_in_kgco2e_saving'] = Decimal(0.0) |
|
637 | ||
638 | if energy_category_set is not None and len(energy_category_set) > 0: |
|
639 | for energy_category_id in energy_category_set: |
|
640 | result['reporting_period']['names'].append(energy_category_dict[energy_category_id]['name']) |
|
641 | result['reporting_period']['energy_category_ids'].append(energy_category_id) |
|
642 | result['reporting_period']['units'].append(energy_category_dict[energy_category_id]['unit_of_measure']) |
|
643 | result['reporting_period']['timestamps'].append(reporting[energy_category_id]['timestamps']) |
|
644 | result['reporting_period']['values_saving'].append(reporting[energy_category_id]['values_saving']) |
|
645 | result['reporting_period']['subtotals_saving'].append(reporting[energy_category_id]['subtotal_saving']) |
|
646 | result['reporting_period']['subtotals_in_kgce_saving'].append( |
|
647 | reporting[energy_category_id]['subtotal_in_kgce_saving']) |
|
648 | result['reporting_period']['subtotals_in_kgco2e_saving'].append( |
|
649 | reporting[energy_category_id]['subtotal_in_kgco2e_saving']) |
|
650 | result['reporting_period']['subtotals_per_unit_area_saving'].append( |
|
651 | reporting[energy_category_id]['subtotal_saving'] / shopfloor['area'] if shopfloor['area'] > 0.0 |
|
652 | else None) |
|
653 | result['reporting_period']['increment_rates_saving'].append( |
|
654 | (reporting[energy_category_id]['subtotal_saving'] - base[energy_category_id]['subtotal_saving']) / |
|
655 | base[energy_category_id]['subtotal_saving'] |
|
656 | if base[energy_category_id]['subtotal_saving'] > 0.0 else None) |
|
657 | result['reporting_period']['total_in_kgce_saving'] += \ |
|
658 | reporting[energy_category_id]['subtotal_in_kgce_saving'] |
|
659 | result['reporting_period']['total_in_kgco2e_saving'] += \ |
|
660 | reporting[energy_category_id]['subtotal_in_kgco2e_saving'] |
|
661 | ||
662 | result['reporting_period']['total_in_kgco2e_per_unit_area_saving'] = \ |
|
663 | result['reporting_period']['total_in_kgce_saving'] / shopfloor['area'] if shopfloor['area'] > 0.0 else None |
|
664 | ||
665 | result['reporting_period']['increment_rate_in_kgce_saving'] = \ |
|
666 | (result['reporting_period']['total_in_kgce_saving'] - result['base_period']['total_in_kgce_saving']) / \ |
|
667 | result['base_period']['total_in_kgce_saving'] \ |
|
668 | if result['base_period']['total_in_kgce_saving'] > Decimal(0.0) else None |
|
669 | ||
670 | result['reporting_period']['total_in_kgce_per_unit_area_saving'] = \ |
|
671 | result['reporting_period']['total_in_kgco2e_saving'] / shopfloor['area'] \ |
|
672 | if shopfloor['area'] > 0.0 else None |
|
673 | ||
674 | result['reporting_period']['increment_rate_in_kgco2e_saving'] = \ |
|
675 | (result['reporting_period']['total_in_kgco2e_saving'] - result['base_period']['total_in_kgco2e_saving']) / \ |
|
676 | result['base_period']['total_in_kgco2e_saving'] \ |
|
677 | if result['base_period']['total_in_kgco2e_saving'] > Decimal(0.0) else None |
|
678 | ||
679 | result['parameters'] = { |
|
680 | "names": parameters_data['names'], |
|
681 | "timestamps": parameters_data['timestamps'], |
|
682 | "values": parameters_data['values'] |
|
683 | } |
|
684 | ||
685 | resp.body = json.dumps(result) |
|
686 |
@@ 10-679 (lines=670) @@ | ||
7 | from decimal import Decimal |
|
8 | ||
9 | ||
10 | class Reporting: |
|
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_START_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_END_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_END_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_START_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_START_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_END_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_END_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_END_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) |
|
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 |