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import re |
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from datetime import datetime, timedelta, timezone |
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from decimal import Decimal |
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import falcon |
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import mysql.connector |
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import simplejson as json |
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import config |
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import excelexporters.shopfloorcost |
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from core import utilities |
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from core.useractivity import access_control, api_key_control |
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View Code Duplication |
class Reporting: |
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def __init__(self): |
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""""Initializes Reporting""" |
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pass |
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@staticmethod |
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def on_options(req, resp): |
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_ = req |
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resp.status = falcon.HTTP_200 |
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#################################################################################################################### |
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# PROCEDURES |
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# Step 1: valid parameters |
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# Step 2: query the shopfloor |
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# Step 3: query energy categories |
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# Step 4: query associated sensors |
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# Step 5: query associated points |
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# Step 6: query base period energy cost |
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# Step 7: query reporting period energy cost |
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# Step 8: query tariff data |
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# Step 9: query associated sensors and points data |
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# Step 10: construct the report |
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#################################################################################################################### |
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@staticmethod |
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def on_get(req, resp): |
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if 'API-KEY' not in req.headers or \ |
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not isinstance(req.headers['API-KEY'], str) or \ |
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len(str.strip(req.headers['API-KEY'])) == 0: |
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access_control(req) |
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else: |
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api_key_control(req) |
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print(req.params) |
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shopfloor_id = req.params.get('shopfloorid') |
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shopfloor_uuid = req.params.get('shopflooruuid') |
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period_type = req.params.get('periodtype') |
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base_period_start_datetime_local = req.params.get('baseperiodstartdatetime') |
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base_period_end_datetime_local = req.params.get('baseperiodenddatetime') |
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reporting_period_start_datetime_local = req.params.get('reportingperiodstartdatetime') |
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reporting_period_end_datetime_local = req.params.get('reportingperiodenddatetime') |
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language = req.params.get('language') |
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quick_mode = req.params.get('quickmode') |
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################################################################################################################ |
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# Step 1: valid parameters |
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################################################################################################################ |
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if shopfloor_id is None and shopfloor_uuid is None: |
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raise falcon.HTTPError(status=falcon.HTTP_400, |
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title='API.BAD_REQUEST', |
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description='API.INVALID_SHOPFLOOR_ID') |
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if shopfloor_id is not None: |
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shopfloor_id = str.strip(shopfloor_id) |
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if not shopfloor_id.isdigit() or int(shopfloor_id) <= 0: |
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raise falcon.HTTPError(status=falcon.HTTP_400, |
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title='API.BAD_REQUEST', |
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description='API.INVALID_SHOPFLOOR_ID') |
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if shopfloor_uuid is not None: |
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regex = re.compile(r'^[a-f0-9]{8}-?[a-f0-9]{4}-?4[a-f0-9]{3}-?[89ab][a-f0-9]{3}-?[a-f0-9]{12}\Z', re.I) |
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match = regex.match(str.strip(shopfloor_uuid)) |
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if not bool(match): |
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raise falcon.HTTPError(status=falcon.HTTP_400, |
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title='API.BAD_REQUEST', |
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description='API.INVALID_SHOPFLOOR_UUID') |
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if period_type is None: |
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raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
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description='API.INVALID_PERIOD_TYPE') |
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else: |
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period_type = str.strip(period_type) |
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if period_type not in ['hourly', 'daily', 'weekly', 'monthly', 'yearly']: |
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raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
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description='API.INVALID_PERIOD_TYPE') |
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timezone_offset = int(config.utc_offset[1:3]) * 60 + int(config.utc_offset[4:6]) |
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if config.utc_offset[0] == '-': |
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timezone_offset = -timezone_offset |
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base_start_datetime_utc = None |
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if base_period_start_datetime_local is not None and len(str.strip(base_period_start_datetime_local)) > 0: |
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base_period_start_datetime_local = str.strip(base_period_start_datetime_local) |
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try: |
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base_start_datetime_utc = datetime.strptime(base_period_start_datetime_local, '%Y-%m-%dT%H:%M:%S') |
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except ValueError: |
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raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
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description="API.INVALID_BASE_PERIOD_START_DATETIME") |
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base_start_datetime_utc = \ |
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base_start_datetime_utc.replace(tzinfo=timezone.utc) - timedelta(minutes=timezone_offset) |
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# nomalize the start datetime |
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if config.minutes_to_count == 30 and base_start_datetime_utc.minute >= 30: |
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base_start_datetime_utc = base_start_datetime_utc.replace(minute=30, second=0, microsecond=0) |
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else: |
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base_start_datetime_utc = base_start_datetime_utc.replace(minute=0, second=0, microsecond=0) |
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base_end_datetime_utc = None |
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if base_period_end_datetime_local is not None and len(str.strip(base_period_end_datetime_local)) > 0: |
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base_period_end_datetime_local = str.strip(base_period_end_datetime_local) |
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try: |
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base_end_datetime_utc = datetime.strptime(base_period_end_datetime_local, '%Y-%m-%dT%H:%M:%S') |
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except ValueError: |
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raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
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description="API.INVALID_BASE_PERIOD_END_DATETIME") |
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base_end_datetime_utc = \ |
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base_end_datetime_utc.replace(tzinfo=timezone.utc) - timedelta(minutes=timezone_offset) |
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if base_start_datetime_utc is not None and base_end_datetime_utc is not None and \ |
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base_start_datetime_utc >= base_end_datetime_utc: |
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raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
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description='API.INVALID_BASE_PERIOD_END_DATETIME') |
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if reporting_period_start_datetime_local is None: |
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raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
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description="API.INVALID_REPORTING_PERIOD_START_DATETIME") |
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else: |
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reporting_period_start_datetime_local = str.strip(reporting_period_start_datetime_local) |
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try: |
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reporting_start_datetime_utc = datetime.strptime(reporting_period_start_datetime_local, |
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'%Y-%m-%dT%H:%M:%S') |
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except ValueError: |
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raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
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description="API.INVALID_REPORTING_PERIOD_START_DATETIME") |
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reporting_start_datetime_utc = \ |
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reporting_start_datetime_utc.replace(tzinfo=timezone.utc) - timedelta(minutes=timezone_offset) |
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# nomalize the start datetime |
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if config.minutes_to_count == 30 and reporting_start_datetime_utc.minute >= 30: |
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reporting_start_datetime_utc = reporting_start_datetime_utc.replace(minute=30, second=0, microsecond=0) |
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else: |
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reporting_start_datetime_utc = reporting_start_datetime_utc.replace(minute=0, second=0, microsecond=0) |
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if reporting_period_end_datetime_local is None: |
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raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
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description="API.INVALID_REPORTING_PERIOD_END_DATETIME") |
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else: |
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reporting_period_end_datetime_local = str.strip(reporting_period_end_datetime_local) |
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try: |
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reporting_end_datetime_utc = datetime.strptime(reporting_period_end_datetime_local, |
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'%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ |
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timedelta(minutes=timezone_offset) |
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except ValueError: |
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raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
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description="API.INVALID_REPORTING_PERIOD_END_DATETIME") |
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if reporting_start_datetime_utc >= reporting_end_datetime_utc: |
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raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', |
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description='API.INVALID_REPORTING_PERIOD_END_DATETIME') |
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# if turn quick mode on, do not return parameters data and excel file |
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is_quick_mode = False |
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if quick_mode is not None and \ |
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len(str.strip(quick_mode)) > 0 and \ |
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str.lower(str.strip(quick_mode)) in ('true', 't', 'on', 'yes', 'y'): |
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is_quick_mode = True |
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trans = utilities.get_translation(language) |
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trans.install() |
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_ = trans.gettext |
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################################################################################################################ |
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# Step 2: query the shopfloor |
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################################################################################################################ |
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cnx_system = mysql.connector.connect(**config.myems_system_db) |
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cursor_system = cnx_system.cursor() |
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cnx_billing = mysql.connector.connect(**config.myems_billing_db) |
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cursor_billing = cnx_billing.cursor() |
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cnx_historical = mysql.connector.connect(**config.myems_historical_db) |
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cursor_historical = cnx_historical.cursor() |
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if shopfloor_id is not None: |
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cursor_system.execute(" SELECT id, name, area, cost_center_id " |
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" FROM tbl_shopfloors " |
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" WHERE id = %s ", (shopfloor_id,)) |
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row_shopfloor = cursor_system.fetchone() |
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elif shopfloor_uuid is not None: |
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cursor_system.execute(" SELECT id, name, area, cost_center_id " |
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" FROM tbl_shopfloors " |
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" WHERE uuid = %s ", (shopfloor_uuid,)) |
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row_shopfloor = cursor_system.fetchone() |
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if row_shopfloor is None: |
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if cursor_system: |
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cursor_system.close() |
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if cnx_system: |
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cnx_system.close() |
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if cursor_billing: |
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cursor_billing.close() |
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if cnx_billing: |
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cnx_billing.close() |
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if cursor_historical: |
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cursor_historical.close() |
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if cnx_historical: |
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cnx_historical.close() |
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raise falcon.HTTPError(status=falcon.HTTP_404, title='API.NOT_FOUND', description='API.SHOPFLOOR_NOT_FOUND') |
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shopfloor = dict() |
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shopfloor['id'] = row_shopfloor[0] |
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shopfloor['name'] = row_shopfloor[1] |
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shopfloor['area'] = row_shopfloor[2] |
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shopfloor['cost_center_id'] = row_shopfloor[3] |
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################################################################################################################ |
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# Step 3: query energy categories |
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################################################################################################################ |
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energy_category_set = set() |
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# query energy categories in base period |
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cursor_billing.execute(" SELECT DISTINCT(energy_category_id) " |
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" FROM tbl_shopfloor_input_category_hourly " |
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" WHERE shopfloor_id = %s " |
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" AND start_datetime_utc >= %s " |
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" AND start_datetime_utc < %s ", |
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(shopfloor['id'], base_start_datetime_utc, base_end_datetime_utc)) |
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rows_energy_categories = cursor_billing.fetchall() |
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if rows_energy_categories is not None and len(rows_energy_categories) > 0: |
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for row_energy_category in rows_energy_categories: |
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energy_category_set.add(row_energy_category[0]) |
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# query energy categories in reporting period |
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cursor_billing.execute(" SELECT DISTINCT(energy_category_id) " |
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" FROM tbl_shopfloor_input_category_hourly " |
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" WHERE shopfloor_id = %s " |
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" AND start_datetime_utc >= %s " |
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" AND start_datetime_utc < %s ", |
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(shopfloor['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) |
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rows_energy_categories = cursor_billing.fetchall() |
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if rows_energy_categories is not None and len(rows_energy_categories) > 0: |
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for row_energy_category in rows_energy_categories: |
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energy_category_set.add(row_energy_category[0]) |
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# query all energy categories in base period and reporting period |
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cursor_system.execute(" SELECT id, name, unit_of_measure, kgce, kgco2e " |
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" FROM tbl_energy_categories " |
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" ORDER BY id ", ) |
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rows_energy_categories = cursor_system.fetchall() |
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if rows_energy_categories is None or len(rows_energy_categories) == 0: |
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if cursor_system: |
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cursor_system.close() |
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if cnx_system: |
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cnx_system.close() |
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if cursor_billing: |
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cursor_billing.close() |
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if cnx_billing: |
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cnx_billing.close() |
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if cursor_historical: |
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cursor_historical.close() |
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if cnx_historical: |
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cnx_historical.close() |
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raise falcon.HTTPError(status=falcon.HTTP_404, |
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title='API.NOT_FOUND', |
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description='API.ENERGY_CATEGORY_NOT_FOUND') |
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energy_category_dict = dict() |
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for row_energy_category in rows_energy_categories: |
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if row_energy_category[0] in energy_category_set: |
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energy_category_dict[row_energy_category[0]] = {"name": row_energy_category[1], |
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"unit_of_measure": row_energy_category[2], |
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"kgce": row_energy_category[3], |
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"kgco2e": row_energy_category[4]} |
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################################################################################################################ |
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# Step 4: query associated sensors |
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################################################################################################################ |
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point_list = list() |
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cursor_system.execute(" SELECT p.id, p.name, p.units, p.object_type " |
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" FROM tbl_shopfloors st, tbl_sensors se, tbl_shopfloors_sensors ss, " |
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" tbl_points p, tbl_sensors_points sp " |
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" WHERE st.id = %s AND st.id = ss.shopfloor_id AND ss.sensor_id = se.id " |
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" AND se.id = sp.sensor_id AND sp.point_id = p.id " |
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" ORDER BY p.id ", (shopfloor['id'],)) |
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rows_points = cursor_system.fetchall() |
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if rows_points is not None and len(rows_points) > 0: |
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for row in rows_points: |
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point_list.append({"id": row[0], "name": row[1], "units": row[2], "object_type": row[3]}) |
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################################################################################################################ |
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# Step 5: query associated points |
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################################################################################################################ |
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cursor_system.execute(" SELECT p.id, p.name, p.units, p.object_type " |
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" FROM tbl_shopfloors s, tbl_shopfloors_points sp, tbl_points p " |
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" WHERE s.id = %s AND s.id = sp.shopfloor_id AND sp.point_id = p.id " |
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" ORDER BY p.id ", (shopfloor['id'],)) |
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rows_points = cursor_system.fetchall() |
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if rows_points is not None and len(rows_points) > 0: |
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for row in rows_points: |
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point_list.append({"id": row[0], "name": row[1], "units": row[2], "object_type": row[3]}) |
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|
302
|
|
|
################################################################################################################ |
303
|
|
|
# Step 6: query base period energy cost |
304
|
|
|
################################################################################################################ |
305
|
|
|
base = dict() |
306
|
|
|
if energy_category_set is not None and len(energy_category_set) > 0: |
307
|
|
|
for energy_category_id in energy_category_set: |
308
|
|
|
base[energy_category_id] = dict() |
309
|
|
|
base[energy_category_id]['timestamps'] = list() |
310
|
|
|
base[energy_category_id]['values'] = list() |
311
|
|
|
base[energy_category_id]['subtotal'] = Decimal(0.0) |
312
|
|
|
|
313
|
|
|
cursor_billing.execute(" SELECT start_datetime_utc, actual_value " |
314
|
|
|
" FROM tbl_shopfloor_input_category_hourly " |
315
|
|
|
" WHERE shopfloor_id = %s " |
316
|
|
|
" AND energy_category_id = %s " |
317
|
|
|
" AND start_datetime_utc >= %s " |
318
|
|
|
" AND start_datetime_utc < %s " |
319
|
|
|
" ORDER BY start_datetime_utc ", |
320
|
|
|
(shopfloor['id'], |
321
|
|
|
energy_category_id, |
322
|
|
|
base_start_datetime_utc, |
323
|
|
|
base_end_datetime_utc)) |
324
|
|
|
rows_shopfloor_hourly = cursor_billing.fetchall() |
325
|
|
|
|
326
|
|
|
rows_shopfloor_periodically = utilities.aggregate_hourly_data_by_period(rows_shopfloor_hourly, |
327
|
|
|
base_start_datetime_utc, |
328
|
|
|
base_end_datetime_utc, |
329
|
|
|
period_type) |
330
|
|
|
for row_shopfloor_periodically in rows_shopfloor_periodically: |
331
|
|
|
current_datetime_local = row_shopfloor_periodically[0].replace(tzinfo=timezone.utc) + \ |
332
|
|
|
timedelta(minutes=timezone_offset) |
333
|
|
|
if period_type == 'hourly': |
334
|
|
|
current_datetime = current_datetime_local.isoformat()[0:19] |
335
|
|
|
elif period_type == 'daily': |
336
|
|
|
current_datetime = current_datetime_local.isoformat()[0:10] |
337
|
|
|
elif period_type == 'weekly': |
338
|
|
|
current_datetime = current_datetime_local.isoformat()[0:10] |
339
|
|
|
elif period_type == 'monthly': |
340
|
|
|
current_datetime = current_datetime_local.isoformat()[0:7] |
341
|
|
|
elif period_type == 'yearly': |
342
|
|
|
current_datetime = current_datetime_local.isoformat()[0:4] |
343
|
|
|
|
344
|
|
|
actual_value = Decimal(0.0) if row_shopfloor_periodically[1] is None \ |
345
|
|
|
else row_shopfloor_periodically[1] |
346
|
|
|
base[energy_category_id]['timestamps'].append(current_datetime) |
|
|
|
|
347
|
|
|
base[energy_category_id]['values'].append(actual_value) |
348
|
|
|
base[energy_category_id]['subtotal'] += actual_value |
349
|
|
|
|
350
|
|
|
################################################################################################################ |
351
|
|
|
# Step 7: query reporting period energy cost |
352
|
|
|
################################################################################################################ |
353
|
|
|
reporting = dict() |
354
|
|
|
if energy_category_set is not None and len(energy_category_set) > 0: |
355
|
|
|
for energy_category_id in energy_category_set: |
356
|
|
|
reporting[energy_category_id] = dict() |
357
|
|
|
reporting[energy_category_id]['timestamps'] = list() |
358
|
|
|
reporting[energy_category_id]['values'] = list() |
359
|
|
|
reporting[energy_category_id]['subtotal'] = Decimal(0.0) |
360
|
|
|
reporting[energy_category_id]['toppeak'] = Decimal(0.0) |
361
|
|
|
reporting[energy_category_id]['onpeak'] = Decimal(0.0) |
362
|
|
|
reporting[energy_category_id]['midpeak'] = Decimal(0.0) |
363
|
|
|
reporting[energy_category_id]['offpeak'] = Decimal(0.0) |
364
|
|
|
reporting[energy_category_id]['deep'] = Decimal(0.0) |
365
|
|
|
|
366
|
|
|
cursor_billing.execute(" SELECT start_datetime_utc, actual_value " |
367
|
|
|
" FROM tbl_shopfloor_input_category_hourly " |
368
|
|
|
" WHERE shopfloor_id = %s " |
369
|
|
|
" AND energy_category_id = %s " |
370
|
|
|
" AND start_datetime_utc >= %s " |
371
|
|
|
" AND start_datetime_utc < %s " |
372
|
|
|
" ORDER BY start_datetime_utc ", |
373
|
|
|
(shopfloor['id'], |
374
|
|
|
energy_category_id, |
375
|
|
|
reporting_start_datetime_utc, |
376
|
|
|
reporting_end_datetime_utc)) |
377
|
|
|
rows_shopfloor_hourly = cursor_billing.fetchall() |
378
|
|
|
|
379
|
|
|
rows_shopfloor_periodically = utilities.aggregate_hourly_data_by_period(rows_shopfloor_hourly, |
380
|
|
|
reporting_start_datetime_utc, |
381
|
|
|
reporting_end_datetime_utc, |
382
|
|
|
period_type) |
383
|
|
|
for row_shopfloor_periodically in rows_shopfloor_periodically: |
384
|
|
|
current_datetime_local = row_shopfloor_periodically[0].replace(tzinfo=timezone.utc) + \ |
385
|
|
|
timedelta(minutes=timezone_offset) |
386
|
|
|
if period_type == 'hourly': |
387
|
|
|
current_datetime = current_datetime_local.isoformat()[0:19] |
388
|
|
|
elif period_type == 'daily': |
389
|
|
|
current_datetime = current_datetime_local.isoformat()[0:10] |
390
|
|
|
elif period_type == 'weekly': |
391
|
|
|
current_datetime = current_datetime_local.isoformat()[0:10] |
392
|
|
|
elif period_type == 'monthly': |
393
|
|
|
current_datetime = current_datetime_local.isoformat()[0:7] |
394
|
|
|
elif period_type == 'yearly': |
395
|
|
|
current_datetime = current_datetime_local.isoformat()[0:4] |
396
|
|
|
|
397
|
|
|
actual_value = Decimal(0.0) if row_shopfloor_periodically[1] is None \ |
398
|
|
|
else row_shopfloor_periodically[1] |
399
|
|
|
reporting[energy_category_id]['timestamps'].append(current_datetime) |
400
|
|
|
reporting[energy_category_id]['values'].append(actual_value) |
401
|
|
|
reporting[energy_category_id]['subtotal'] += actual_value |
402
|
|
|
|
403
|
|
|
energy_category_tariff_dict = utilities.get_energy_category_peak_types(shopfloor['cost_center_id'], |
404
|
|
|
energy_category_id, |
405
|
|
|
reporting_start_datetime_utc, |
406
|
|
|
reporting_end_datetime_utc) |
407
|
|
|
for row in rows_shopfloor_hourly: |
408
|
|
|
peak_type = energy_category_tariff_dict.get(row[0], None) |
409
|
|
|
if peak_type == 'toppeak': |
410
|
|
|
reporting[energy_category_id]['toppeak'] += row[1] |
411
|
|
|
elif peak_type == 'onpeak': |
412
|
|
|
reporting[energy_category_id]['onpeak'] += row[1] |
413
|
|
|
elif peak_type == 'midpeak': |
414
|
|
|
reporting[energy_category_id]['midpeak'] += row[1] |
415
|
|
|
elif peak_type == 'offpeak': |
416
|
|
|
reporting[energy_category_id]['offpeak'] += row[1] |
417
|
|
|
elif peak_type == 'deep': |
418
|
|
|
reporting[energy_category_id]['deep'] += row[1] |
419
|
|
|
|
420
|
|
|
################################################################################################################ |
421
|
|
|
# Step 8: query tariff data |
422
|
|
|
################################################################################################################ |
423
|
|
|
parameters_data = dict() |
424
|
|
|
parameters_data['names'] = list() |
425
|
|
|
parameters_data['timestamps'] = list() |
426
|
|
|
parameters_data['values'] = list() |
427
|
|
|
if config.is_tariff_appended and energy_category_set is not None and len(energy_category_set) > 0 \ |
428
|
|
|
and not is_quick_mode: |
429
|
|
|
for energy_category_id in energy_category_set: |
430
|
|
|
energy_category_tariff_dict = utilities.get_energy_category_tariffs(shopfloor['cost_center_id'], |
431
|
|
|
energy_category_id, |
432
|
|
|
reporting_start_datetime_utc, |
433
|
|
|
reporting_end_datetime_utc) |
434
|
|
|
tariff_timestamp_list = list() |
435
|
|
|
tariff_value_list = list() |
436
|
|
|
for k, v in energy_category_tariff_dict.items(): |
437
|
|
|
# convert k from utc to local |
438
|
|
|
k = k + timedelta(minutes=timezone_offset) |
439
|
|
|
tariff_timestamp_list.append(k.isoformat()[0:19]) |
440
|
|
|
tariff_value_list.append(v) |
441
|
|
|
|
442
|
|
|
parameters_data['names'].append(_('Tariff') + '-' + energy_category_dict[energy_category_id]['name']) |
443
|
|
|
parameters_data['timestamps'].append(tariff_timestamp_list) |
444
|
|
|
parameters_data['values'].append(tariff_value_list) |
445
|
|
|
|
446
|
|
|
################################################################################################################ |
447
|
|
|
# Step 9: query associated sensors and points data |
448
|
|
|
################################################################################################################ |
449
|
|
|
if not is_quick_mode: |
450
|
|
|
for point in point_list: |
451
|
|
|
point_values = [] |
452
|
|
|
point_timestamps = [] |
453
|
|
|
if point['object_type'] == 'ENERGY_VALUE': |
454
|
|
|
query = (" SELECT utc_date_time, actual_value " |
455
|
|
|
" FROM tbl_energy_value " |
456
|
|
|
" WHERE point_id = %s " |
457
|
|
|
" AND utc_date_time BETWEEN %s AND %s " |
458
|
|
|
" ORDER BY utc_date_time ") |
459
|
|
|
cursor_historical.execute(query, (point['id'], |
460
|
|
|
reporting_start_datetime_utc, |
461
|
|
|
reporting_end_datetime_utc)) |
462
|
|
|
rows = cursor_historical.fetchall() |
463
|
|
|
|
464
|
|
|
if rows is not None and len(rows) > 0: |
465
|
|
|
for row in rows: |
466
|
|
|
current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ |
467
|
|
|
timedelta(minutes=timezone_offset) |
468
|
|
|
current_datetime = current_datetime_local.isoformat()[0:19] |
469
|
|
|
point_timestamps.append(current_datetime) |
470
|
|
|
point_values.append(row[1]) |
471
|
|
|
elif point['object_type'] == 'ANALOG_VALUE': |
472
|
|
|
query = (" SELECT utc_date_time, actual_value " |
473
|
|
|
" FROM tbl_analog_value " |
474
|
|
|
" WHERE point_id = %s " |
475
|
|
|
" AND utc_date_time BETWEEN %s AND %s " |
476
|
|
|
" ORDER BY utc_date_time ") |
477
|
|
|
cursor_historical.execute(query, (point['id'], |
478
|
|
|
reporting_start_datetime_utc, |
479
|
|
|
reporting_end_datetime_utc)) |
480
|
|
|
rows = cursor_historical.fetchall() |
481
|
|
|
|
482
|
|
|
if rows is not None and len(rows) > 0: |
483
|
|
|
for row in rows: |
484
|
|
|
current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ |
485
|
|
|
timedelta(minutes=timezone_offset) |
486
|
|
|
current_datetime = current_datetime_local.isoformat()[0:19] |
487
|
|
|
point_timestamps.append(current_datetime) |
488
|
|
|
point_values.append(row[1]) |
489
|
|
|
elif point['object_type'] == 'DIGITAL_VALUE': |
490
|
|
|
query = (" SELECT utc_date_time, actual_value " |
491
|
|
|
" FROM tbl_digital_value " |
492
|
|
|
" WHERE point_id = %s " |
493
|
|
|
" AND utc_date_time BETWEEN %s AND %s " |
494
|
|
|
" ORDER BY utc_date_time ") |
495
|
|
|
cursor_historical.execute(query, (point['id'], |
496
|
|
|
reporting_start_datetime_utc, |
497
|
|
|
reporting_end_datetime_utc)) |
498
|
|
|
rows = cursor_historical.fetchall() |
499
|
|
|
|
500
|
|
|
if rows is not None and len(rows) > 0: |
501
|
|
|
for row in rows: |
502
|
|
|
current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ |
503
|
|
|
timedelta(minutes=timezone_offset) |
504
|
|
|
current_datetime = current_datetime_local.isoformat()[0:19] |
505
|
|
|
point_timestamps.append(current_datetime) |
506
|
|
|
point_values.append(row[1]) |
507
|
|
|
|
508
|
|
|
parameters_data['names'].append(point['name'] + ' (' + point['units'] + ')') |
509
|
|
|
parameters_data['timestamps'].append(point_timestamps) |
510
|
|
|
parameters_data['values'].append(point_values) |
511
|
|
|
|
512
|
|
|
################################################################################################################ |
513
|
|
|
# Step 10: construct the report |
514
|
|
|
################################################################################################################ |
515
|
|
|
if cursor_system: |
516
|
|
|
cursor_system.close() |
517
|
|
|
if cnx_system: |
518
|
|
|
cnx_system.close() |
519
|
|
|
|
520
|
|
|
if cursor_billing: |
521
|
|
|
cursor_billing.close() |
522
|
|
|
if cnx_billing: |
523
|
|
|
cnx_billing.close() |
524
|
|
|
|
525
|
|
|
if cursor_historical: |
526
|
|
|
cursor_historical.close() |
527
|
|
|
if cnx_historical: |
528
|
|
|
cnx_historical.close() |
529
|
|
|
|
530
|
|
|
result = dict() |
531
|
|
|
|
532
|
|
|
result['shopfloor'] = dict() |
533
|
|
|
result['shopfloor']['name'] = shopfloor['name'] |
534
|
|
|
result['shopfloor']['area'] = shopfloor['area'] |
535
|
|
|
|
536
|
|
|
result['base_period'] = dict() |
537
|
|
|
result['base_period']['names'] = list() |
538
|
|
|
result['base_period']['units'] = list() |
539
|
|
|
result['base_period']['timestamps'] = list() |
540
|
|
|
result['base_period']['values'] = list() |
541
|
|
|
result['base_period']['subtotals'] = list() |
542
|
|
|
result['base_period']['total'] = Decimal(0.0) |
543
|
|
|
if energy_category_set is not None and len(energy_category_set) > 0: |
544
|
|
|
for energy_category_id in energy_category_set: |
545
|
|
|
result['base_period']['names'].append(energy_category_dict[energy_category_id]['name']) |
546
|
|
|
result['base_period']['units'].append(config.currency_unit) |
547
|
|
|
result['base_period']['timestamps'].append(base[energy_category_id]['timestamps']) |
548
|
|
|
result['base_period']['values'].append(base[energy_category_id]['values']) |
549
|
|
|
result['base_period']['subtotals'].append(base[energy_category_id]['subtotal']) |
550
|
|
|
result['base_period']['total'] += base[energy_category_id]['subtotal'] |
551
|
|
|
|
552
|
|
|
result['reporting_period'] = dict() |
553
|
|
|
result['reporting_period']['names'] = list() |
554
|
|
|
result['reporting_period']['energy_category_ids'] = list() |
555
|
|
|
result['reporting_period']['units'] = list() |
556
|
|
|
result['reporting_period']['timestamps'] = list() |
557
|
|
|
result['reporting_period']['values'] = list() |
558
|
|
|
result['reporting_period']['rates'] = list() |
559
|
|
|
result['reporting_period']['subtotals'] = list() |
560
|
|
|
result['reporting_period']['subtotals_per_unit_area'] = list() |
561
|
|
|
result['reporting_period']['toppeaks'] = list() |
562
|
|
|
result['reporting_period']['onpeaks'] = list() |
563
|
|
|
result['reporting_period']['midpeaks'] = list() |
564
|
|
|
result['reporting_period']['offpeaks'] = list() |
565
|
|
|
result['reporting_period']['deeps'] = list() |
566
|
|
|
result['reporting_period']['increment_rates'] = list() |
567
|
|
|
result['reporting_period']['total'] = Decimal(0.0) |
568
|
|
|
result['reporting_period']['total_per_unit_area'] = Decimal(0.0) |
569
|
|
|
result['reporting_period']['total_increment_rate'] = Decimal(0.0) |
570
|
|
|
result['reporting_period']['total_unit'] = config.currency_unit |
571
|
|
|
|
572
|
|
|
if energy_category_set is not None and len(energy_category_set) > 0: |
573
|
|
|
for energy_category_id in energy_category_set: |
574
|
|
|
result['reporting_period']['names'].append(energy_category_dict[energy_category_id]['name']) |
575
|
|
|
result['reporting_period']['energy_category_ids'].append(energy_category_id) |
576
|
|
|
result['reporting_period']['units'].append(config.currency_unit) |
577
|
|
|
result['reporting_period']['timestamps'].append(reporting[energy_category_id]['timestamps']) |
578
|
|
|
result['reporting_period']['values'].append(reporting[energy_category_id]['values']) |
579
|
|
|
result['reporting_period']['subtotals'].append(reporting[energy_category_id]['subtotal']) |
580
|
|
|
result['reporting_period']['subtotals_per_unit_area'].append( |
581
|
|
|
reporting[energy_category_id]['subtotal'] / shopfloor['area'] if shopfloor['area'] > 0.0 else None) |
582
|
|
|
result['reporting_period']['toppeaks'].append(reporting[energy_category_id]['toppeak']) |
583
|
|
|
result['reporting_period']['onpeaks'].append(reporting[energy_category_id]['onpeak']) |
584
|
|
|
result['reporting_period']['midpeaks'].append(reporting[energy_category_id]['midpeak']) |
585
|
|
|
result['reporting_period']['offpeaks'].append(reporting[energy_category_id]['offpeak']) |
586
|
|
|
result['reporting_period']['deeps'].append(reporting[energy_category_id]['deep']) |
587
|
|
|
result['reporting_period']['increment_rates'].append( |
588
|
|
|
(reporting[energy_category_id]['subtotal'] - base[energy_category_id]['subtotal']) / |
589
|
|
|
base[energy_category_id]['subtotal'] |
590
|
|
|
if base[energy_category_id]['subtotal'] > 0.0 else None) |
591
|
|
|
result['reporting_period']['total'] += reporting[energy_category_id]['subtotal'] |
592
|
|
|
|
593
|
|
|
rate = list() |
594
|
|
|
for index, value in enumerate(reporting[energy_category_id]['values']): |
595
|
|
|
if index < len(base[energy_category_id]['values']) \ |
596
|
|
|
and base[energy_category_id]['values'][index] != 0 and value != 0: |
597
|
|
|
rate.append((value - base[energy_category_id]['values'][index]) |
598
|
|
|
/ base[energy_category_id]['values'][index]) |
599
|
|
|
else: |
600
|
|
|
rate.append(None) |
601
|
|
|
result['reporting_period']['rates'].append(rate) |
602
|
|
|
|
603
|
|
|
result['reporting_period']['total_per_unit_area'] = \ |
604
|
|
|
result['reporting_period']['total'] / shopfloor['area'] if shopfloor['area'] > 0.0 else None |
605
|
|
|
|
606
|
|
|
result['reporting_period']['total_increment_rate'] = \ |
607
|
|
|
(result['reporting_period']['total'] - result['base_period']['total']) / \ |
608
|
|
|
result['base_period']['total'] \ |
609
|
|
|
if result['base_period']['total'] > Decimal(0.0) else None |
610
|
|
|
|
611
|
|
|
result['parameters'] = { |
612
|
|
|
"names": parameters_data['names'], |
613
|
|
|
"timestamps": parameters_data['timestamps'], |
614
|
|
|
"values": parameters_data['values'] |
615
|
|
|
} |
616
|
|
|
# export result to Excel file and then encode the file to base64 string |
617
|
|
|
result['excel_bytes_base64'] = None |
618
|
|
|
if not is_quick_mode: |
619
|
|
|
result['excel_bytes_base64'] = excelexporters.shopfloorcost.export(result, |
620
|
|
|
shopfloor['name'], |
621
|
|
|
base_period_start_datetime_local, |
622
|
|
|
base_period_end_datetime_local, |
623
|
|
|
reporting_period_start_datetime_local, |
624
|
|
|
reporting_period_end_datetime_local, |
625
|
|
|
period_type, |
626
|
|
|
language) |
627
|
|
|
resp.text = json.dumps(result) |
628
|
|
|
|