# This file location doesn't work on the server (see above file path) --> be careful
# Initialize empty bulk request
bulk_rq = []
# Iterate over the rows of the dataframe, adding elements to the bulk request
for index, row in df.iterrows():
# Append facility/instance pairs to bulk request
if row['Temperature']:
bulk_rq.append( { 'facility': row['Facility'], 'instance': row['Temperature'] } )
if row['CO2']:
bulk_rq.append( { 'facility': row['Facility'], 'instance': row['CO2'] } )
# Issue get-bulk request
bulk_rsp = get_bulk( bulk_rq )
# Extract map from get-bulk response
map = bulk_rsp['rsp_map']
# Output column headings
# print( 'Location,Temperature,Temperature Units,CO2,CO2 Units' )
# writes to a new csv file, so we can use pandas on the real-time data
# this file location ALSO DOESN'T WORK ON THE SERVER ---> add in that path /media/ea/Data/Students/jade/buildingEnergyApi/
with open(SERVER_PATH + 'ahs_air_data.csv', mode='w') as ahs_air_data:
temp_writer = csv.writer(ahs_air_data, delimiter=";")
# Iterate over the rows of the dataframe, displaying temperature and CO2 values extracted from map
for index, row in df.iterrows():
def get_bulk_request_df():
bulk_rq = []
# Iterate over the rows of the dataframe, adding elements to the bulk request
for index, row in rooms_and_sensors.iterrows():
# Append facility/instance pairs to bulk request
if row['Temperature']:
bulk_rq.append({
'facility': row['Facility'],
'instance': row['Temperature']
})
if row['CO2']:
bulk_rq.append({
'facility': row['Facility'],
'instance': row['CO2']
})
# Issue get-bulk request
try:
bulk_rsp = get_bulk(bulk_rq)
except requests.exceptions.ConnectionError:
raise ConnectionError(
"Unable to get data from. Are you connected to the right WiFi network?"
)
# Extract map from get-bulk response
map = bulk_rsp['rsp_map']
df_dictionary = {
'room': [],
'temperature': [],
'temperature units': [],
'co2': [],
'co2 units': []
}
# Iterate over the rows of the DataFrame, displaying temperature and CO2 values extracted from map
for index, row in rooms_and_sensors.iterrows():
# Initialize empty display values
temp_value = ''
temp_units = ''
co2_value = ''
co2_units = ''
# Get facility of current row
facility = row['Facility']
# Try to extract current row's temperature and CO2 values from map
if facility in map:
instance = str(row['Temperature'])
if instance and (instance in map[facility]):
rsp = map[facility][instance]
property = rsp['property']
temp_value = int(rsp[property]) if isinstance(
rsp[property], numbers.Number) else ''
temp_units = rsp['units']
instance = str(row['CO2'])
if instance and (instance in map[facility]):
rsp = map[facility][instance]
property = rsp['property']
co2_value = int(rsp[property]) if isinstance(
rsp[property], numbers.Number) else ''
co2_units = rsp['units']
# Output CSV format
df_dictionary['room'].append(row['Label'])
df_dictionary['temperature'].append(temp_value)
df_dictionary['temperature units'].append(temp_units)
df_dictionary['co2'].append(co2_value)
df_dictionary['co2 units'].append(co2_units)
return pd.DataFrame.from_dict(df_dictionary)
# Copyright 2018 Building Energy Gateway. All rights reserved.
import time
import numbers
from building_data_requests import get_bulk
from simple_power_request import request_list
start_time = time.time()
# Issue get-bulk request
bulk_rsp = get_bulk(request_list)
# Extract map from response
response_map = bulk_rsp['rsp_map']
# Iterate through list of requests
for request in request_list:
# Initialize empty display values
value = ''
units = ''
# Get facility of current request
facility = request['facility']
# print( 'facility:', facility )
# Look for facility in response map
if facility in response_map:
# Get instance of current request
instance = request['instance']
# Copyright 2018 Building Energy Gateway. All rights reserved.
from building_data_requests import get_bulk
# Build bulk request (rq) structured as a list of dictionaries
# In each dictionary,
# - 'facility' and 'instance' fields are used by get_bulk()
# - 'label' fields are used by us, when printing the response
rq = [ { 'facility': 'ahs', 'instance': '3007360', 'label': 'AHS Main Power' },
{ 'facility': 'ahs', 'instance': '3001489', 'label': 'AHS 351 Temperature' },
{ 'facility': 'ahs', 'instance': '3001477', 'label': 'AHS 351 CO2' } ]
# Issue the request
bulk_rsp = get_bulk( rq )
# Extract the part of the response that pertains to facility 'ahs'
# It is a dictionary with instances as keys
rsp_instances = bulk_rsp['rsp_map']['ahs']
# Iterate over request; correlate each request item with response data
for rq_item in rq:
# Get instance from current request item
instance = rq_item['instance']
# Extract response data corresponding to the instance
rsp_instance = rsp_instances[instance]
# Print label from request item, value and units from response instance
print( '{0}: {1} {2}'.format( rq_item['label'], int( rsp_instance['presentValue'] ), rsp_instance['units'] ) )
# Load dataframe representing requested view
df = pd.read_csv('csv/' + args.view + '.csv', na_filter=False, comment='#')
# Initialize empty request
bulk_request = []
# Build request
for index, row in df.iterrows():
# Extract facility from row
facility = row.iloc[1]
# Traverse instances in current row
for i in range(2, len(row)):
instance = row.iloc[i]
if instance:
# Add facility/instance pair to request
pair = {'facility': facility, 'instance': instance}
bulk_request.append(pair)
# Issue get-bulk request
bulk_rsp = get_bulk(bulk_request, args.hostname, args.port)
rsp_map = bulk_rsp['rsp_map']
# Return view
print(json.dumps(rsp_map))