myems-api/reports/shopfloorbatch.py
from datetime import datetime, timedelta, timezone
from decimal import Decimal
import falcon
import mysql.connector
import simplejson as json
from anytree import AnyNode, LevelOrderIter
import config
import excelexporters.shopfloorbatch
from core.useractivity import access_control, api_key_control
class Reporting:
@staticmethod
def __init__():
""""Initializes Reporting"""
pass
@staticmethod
def on_options(req, resp):
resp.status = falcon.HTTP_200
####################################################################################################################
# PROCEDURES
# Step 1: valid parameters
# Step 2: build a space tree
# Step 3: query all shopfloors in the space tree
# Step 4: query energy categories
# Step 5: query reporting period energy input
# Step 6: construct the report
####################################################################################################################
@staticmethod
def on_get(req, resp):
if 'API-KEY' not in req.headers or \
not isinstance(req.headers['API-KEY'], str) or \
len(str.strip(req.headers['API-KEY'])) == 0:
access_control(req)
else:
api_key_control(req)
print(req.params)
space_id = req.params.get('spaceid')
reporting_period_start_datetime_local = req.params.get('reportingperiodstartdatetime')
reporting_period_end_datetime_local = req.params.get('reportingperiodenddatetime')
language = req.params.get('language')
quick_mode = req.params.get('quickmode')
################################################################################################################
# Step 1: valid parameters
################################################################################################################
if space_id is None:
raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_SPACE_ID')
else:
space_id = str.strip(space_id)
if not space_id.isdigit() or int(space_id) <= 0:
raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST',
description='API.INVALID_SPACE_ID')
else:
space_id = int(space_id)
timezone_offset = int(config.utc_offset[1:3]) * 60 + int(config.utc_offset[4:6])
if config.utc_offset[0] == '-':
timezone_offset = -timezone_offset
if reporting_period_start_datetime_local is None:
raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST',
description="API.INVALID_REPORTING_PERIOD_START_DATETIME")
else:
reporting_period_start_datetime_local = str.strip(reporting_period_start_datetime_local)
try:
reporting_start_datetime_utc = datetime.strptime(reporting_period_start_datetime_local,
'%Y-%m-%dT%H:%M:%S')
except ValueError:
raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST',
description="API.INVALID_REPORTING_PERIOD_START_DATETIME")
reporting_start_datetime_utc = \
reporting_start_datetime_utc.replace(tzinfo=timezone.utc) - timedelta(minutes=timezone_offset)
# nomalize the start datetime
if config.minutes_to_count == 30 and reporting_start_datetime_utc.minute >= 30:
reporting_start_datetime_utc = reporting_start_datetime_utc.replace(minute=30, second=0, microsecond=0)
else:
reporting_start_datetime_utc = reporting_start_datetime_utc.replace(minute=0, second=0, microsecond=0)
if reporting_period_end_datetime_local is None:
raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST',
description="API.INVALID_REPORTING_PERIOD_END_DATETIME")
else:
reporting_period_end_datetime_local = str.strip(reporting_period_end_datetime_local)
try:
reporting_end_datetime_utc = datetime.strptime(reporting_period_end_datetime_local,
'%Y-%m-%dT%H:%M:%S')
except ValueError:
raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST',
description="API.INVALID_REPORTING_PERIOD_END_DATETIME")
reporting_end_datetime_utc = reporting_end_datetime_utc.replace(tzinfo=timezone.utc) - \
timedelta(minutes=timezone_offset)
if reporting_start_datetime_utc >= reporting_end_datetime_utc:
raise falcon.HTTPError(status=falcon.HTTP_400, title='API.BAD_REQUEST',
description='API.INVALID_REPORTING_PERIOD_END_DATETIME')
# if turn quick mode on, do not return parameters data and excel file
is_quick_mode = False
if quick_mode is not None and \
len(str.strip(quick_mode)) > 0 and \
str.lower(str.strip(quick_mode)) in ('true', 't', 'on', 'yes', 'y'):
is_quick_mode = True
cnx_system_db = mysql.connector.connect(**config.myems_system_db)
cursor_system_db = cnx_system_db.cursor()
cursor_system_db.execute(" SELECT name "
" FROM tbl_spaces "
" WHERE id = %s ", (space_id,))
row = cursor_system_db.fetchone()
if row is None:
if cursor_system_db:
cursor_system_db.close()
if cnx_system_db:
cnx_system_db.close()
raise falcon.HTTPError(status=falcon.HTTP_404, title='API.NOT_FOUND',
description='API.SPACE_NOT_FOUND')
else:
space_name = row[0]
################################################################################################################
# Step 2: build a space tree
################################################################################################################
query = (" SELECT id, name, parent_space_id "
" FROM tbl_spaces "
" ORDER BY id ")
cursor_system_db.execute(query)
rows_spaces = cursor_system_db.fetchall()
node_dict = dict()
if rows_spaces is not None and len(rows_spaces) > 0:
for row in rows_spaces:
parent_node = node_dict[row[2]] if row[2] is not None else None
node_dict[row[0]] = AnyNode(id=row[0], parent=parent_node, name=row[1])
################################################################################################################
# Step 3: query all shopfloors in the space tree
################################################################################################################
shopfloor_dict = dict()
space_dict = dict()
for node in LevelOrderIter(node_dict[space_id]):
space_dict[node.id] = node.name
cursor_system_db.execute(" SELECT shopfloor.id, shopfloor.name AS shopfloor_name, "
" shopfloor.uuid AS shopfloor_uuid, s.name AS space_name, "
" cc.name AS cost_center_name, shopfloor.description "
" FROM tbl_spaces s, tbl_spaces_shopfloors ss,"
" tbl_shopfloors shopfloor, tbl_cost_centers cc "
" WHERE s.id IN ( " + ', '.join(map(str, space_dict.keys())) + ") "
" AND ss.space_id = s.id AND ss.shopfloor_id = shopfloor.id "
" AND shopfloor.cost_center_id = cc.id ", )
rows_shopfloors = cursor_system_db.fetchall()
if rows_shopfloors is not None and len(rows_shopfloors) > 0:
for row in rows_shopfloors:
shopfloor_dict[row[0]] = {"shopfloor_name": row[1],
"shopfloor_uuid": row[2],
"space_name": row[3],
"cost_center_name": row[4],
"description": row[5],
"values": list()}
################################################################################################################
# Step 4: query energy categories
################################################################################################################
cnx_energy_db = mysql.connector.connect(**config.myems_energy_db)
cursor_energy_db = cnx_energy_db.cursor()
# query energy categories in reporting period
energy_category_set = set()
cursor_energy_db.execute(" SELECT DISTINCT(energy_category_id) "
" FROM tbl_shopfloor_input_category_hourly "
" WHERE start_datetime_utc >= %s AND start_datetime_utc < %s ",
(reporting_start_datetime_utc, reporting_end_datetime_utc))
rows_energy_categories = cursor_energy_db.fetchall()
if rows_energy_categories is not None and len(rows_energy_categories) > 0:
for row_energy_category in rows_energy_categories:
energy_category_set.add(row_energy_category[0])
# query all energy categories
cursor_system_db.execute(" SELECT id, name, unit_of_measure "
" FROM tbl_energy_categories "
" ORDER BY id ", )
rows_energy_categories = cursor_system_db.fetchall()
if rows_energy_categories is None or len(rows_energy_categories) == 0:
if cursor_system_db:
cursor_system_db.close()
if cnx_system_db:
cnx_system_db.close()
if cursor_energy_db:
cursor_energy_db.close()
if cnx_energy_db:
cnx_energy_db.close()
raise falcon.HTTPError(status=falcon.HTTP_404,
title='API.NOT_FOUND',
description='API.ENERGY_CATEGORY_NOT_FOUND')
energy_category_list = list()
for row_energy_category in rows_energy_categories:
if row_energy_category[0] in energy_category_set:
energy_category_list.append({"id": row_energy_category[0],
"name": row_energy_category[1],
"unit_of_measure": row_energy_category[2]})
################################################################################################################
# Step 5: query reporting period energy input
################################################################################################################
for shopfloor_id in shopfloor_dict:
cursor_energy_db.execute(" SELECT energy_category_id, SUM(actual_value) "
" FROM tbl_shopfloor_input_category_hourly "
" WHERE shopfloor_id = %s "
" AND start_datetime_utc >= %s "
" AND start_datetime_utc < %s "
" GROUP BY energy_category_id ",
(shopfloor_id,
reporting_start_datetime_utc,
reporting_end_datetime_utc))
rows_shopfloor_energy = cursor_energy_db.fetchall()
for energy_category in energy_category_list:
subtotal = Decimal(0.0)
for row_shopfloor_energy in rows_shopfloor_energy:
if energy_category['id'] == row_shopfloor_energy[0]:
subtotal = row_shopfloor_energy[1]
break
shopfloor_dict[shopfloor_id]['values'].append(subtotal)
if cursor_system_db:
cursor_system_db.close()
if cnx_system_db:
cnx_system_db.close()
if cursor_energy_db:
cursor_energy_db.close()
if cnx_energy_db:
cnx_energy_db.close()
################################################################################################################
# Step 6: construct the report
################################################################################################################
shopfloor_list = list()
for shopfloor_id, shopfloor in shopfloor_dict.items():
shopfloor_list.append({
"id": shopfloor_id,
"shopfloor_name": shopfloor['shopfloor_name'],
"shopfloor_uuid": shopfloor['shopfloor_uuid'],
"space_name": shopfloor['space_name'],
"cost_center_name": shopfloor['cost_center_name'],
"description": shopfloor['description'],
"values": shopfloor['values'],
})
result = {'shopfloors': shopfloor_list, 'energycategories': energy_category_list, 'excel_bytes_base64': None}
# export result to Excel file and then encode the file to base64 string
if not is_quick_mode:
result['excel_bytes_base64'] = excelexporters.shopfloorbatch.export(result,
space_name,
reporting_period_start_datetime_local,
reporting_period_end_datetime_local,
language)
resp.text = json.dumps(result)