def return_output_usage(dict_outputs, table_misc, outputs,
table_output_channels,
custom_options_values_output_channels):
"""Return output usage and cost."""
date_now = datetime.date.today()
time_now = datetime.datetime.now()
past_month_seconds = 0
if table_misc.output_usage_dayofmonth == datetime.datetime.today().day:
past_month_seconds = (time_now - time_now.replace(
hour=0, minute=0, second=0, microsecond=0)).total_seconds()
elif table_misc.output_usage_dayofmonth > datetime.datetime.today().day:
first_day = date_now.replace(day=1)
last_month = first_day - datetime.timedelta(days=1)
past_month = last_month.replace(day=table_misc.output_usage_dayofmonth)
past_month_seconds = (date_now - past_month).total_seconds()
elif table_misc.output_usage_dayofmonth < datetime.datetime.today().day:
past_month = date_now.replace(day=table_misc.output_usage_dayofmonth)
past_month_seconds = (date_now - past_month).total_seconds()
output_stats = OrderedDict()
# Calculate output on duration for different time periods
# Use OrderedDict to ensure proper order when saved to csv file
output_stats['total_duration'] = dict.fromkeys(
['1d', '1w', '1m', '1m_date', '1y'], 0)
output_stats['total_kwh'] = dict.fromkeys(
['1d', '1w', '1m', '1m_date', '1y'], 0)
output_stats['total_cost'] = dict.fromkeys(
['1d', '1w', '1m', '1m_date', '1y'], 0)
for each_output in outputs:
output_channels = table_output_channels.query.filter(
table_output_channels.output_id == each_output.unique_id).all()
for each_channel in output_channels:
channel_options = custom_options_values_output_channels[
each_output.unique_id][each_channel.channel]
if ('types' in dict_outputs[each_output.output_type]
['channels_dict'][each_channel.channel]
and 'on_off' in dict_outputs[each_output.output_type]
['channels_dict'][each_channel.channel]['types']
and 'amps' in channel_options):
past_1d_hours = output_sec_on(
each_output.unique_id,
86400,
output_channel=each_channel.channel) / 3600
past_1w_hours = output_sec_on(
each_output.unique_id,
604800,
output_channel=each_channel.channel) / 3600
past_1m_hours = output_sec_on(
each_output.unique_id,
2629743,
output_channel=each_channel.channel) / 3600
past_1m_date_hours = output_sec_on(
each_output.unique_id,
int(past_month_seconds),
output_channel=each_channel.channel) / 3600
past_1y_hours = output_sec_on(
each_output.unique_id,
31556926,
output_channel=each_channel.channel) / 3600
past_1d_kwh = table_misc.output_usage_volts * channel_options[
'amps'] * past_1d_hours / 1000
past_1w_kwh = table_misc.output_usage_volts * channel_options[
'amps'] * past_1w_hours / 1000
past_1m_kwh = table_misc.output_usage_volts * channel_options[
'amps'] * past_1m_hours / 1000
past_1m_date_kwh = table_misc.output_usage_volts * channel_options[
'amps'] * past_1m_date_hours / 1000
past_1y_kwh = table_misc.output_usage_volts * channel_options[
'amps'] * past_1y_hours / 1000
if each_output.unique_id not in output_stats:
output_stats[each_output.unique_id] = {}
output_stats[each_output.unique_id][each_channel.unique_id] = {
'1d': {
'hours_on': past_1d_hours,
'kwh': past_1d_kwh,
'cost': table_misc.output_usage_cost * past_1d_kwh
},
'1w': {
'hours_on': past_1w_hours,
'kwh': past_1w_kwh,
'cost': table_misc.output_usage_cost * past_1w_kwh
},
'1m': {
'hours_on': past_1m_hours,
'kwh': past_1m_kwh,
'cost': table_misc.output_usage_cost * past_1m_kwh
},
'1m_date': {
'hours_on': past_1m_date_hours,
'kwh': past_1m_date_kwh,
'cost': table_misc.output_usage_cost * past_1m_date_kwh
},
'1y': {
'hours_on': past_1y_hours,
'kwh': past_1y_kwh,
'cost': table_misc.output_usage_cost * past_1y_kwh
}
}
output_stats['total_duration']['1d'] += past_1d_hours
output_stats['total_duration']['1w'] += past_1w_hours
output_stats['total_duration']['1m'] += past_1m_hours
output_stats['total_duration']['1m_date'] += past_1m_date_hours
output_stats['total_duration']['1y'] += past_1y_hours
output_stats['total_kwh']['1d'] += past_1d_kwh
output_stats['total_kwh']['1w'] += past_1w_kwh
output_stats['total_kwh']['1m'] += past_1m_kwh
output_stats['total_kwh']['1m_date'] += past_1m_date_kwh
output_stats['total_kwh']['1y'] += past_1y_kwh
output_stats['total_cost'][
'1d'] += table_misc.output_usage_cost * past_1d_kwh
output_stats['total_cost'][
'1w'] += table_misc.output_usage_cost * past_1w_kwh
output_stats['total_cost'][
'1m'] += table_misc.output_usage_cost * past_1m_kwh
output_stats['total_cost'][
'1m_date'] += table_misc.output_usage_cost * past_1m_date_kwh
output_stats['total_cost'][
'1y'] += table_misc.output_usage_cost * past_1y_kwh
return output_stats
def return_output_usage(table_misc, table_outputs):
""" Return output usage and cost """
dict_outputs = parse_output_information()
date_now = datetime.date.today()
time_now = datetime.datetime.now()
past_month_seconds = 0
if table_misc.output_usage_dayofmonth == datetime.datetime.today().day:
past_month_seconds = (time_now - time_now.replace(
hour=0, minute=0, second=0, microsecond=0)).total_seconds()
elif table_misc.output_usage_dayofmonth > datetime.datetime.today().day:
first_day = date_now.replace(day=1)
last_month = first_day - datetime.timedelta(days=1)
past_month = last_month.replace(day=table_misc.output_usage_dayofmonth)
past_month_seconds = (date_now - past_month).total_seconds()
elif table_misc.output_usage_dayofmonth < datetime.datetime.today().day:
past_month = date_now.replace(day=table_misc.output_usage_dayofmonth)
past_month_seconds = (date_now - past_month).total_seconds()
output_stats = OrderedDict()
# Calculate output on duration for different time periods
# Use OrderedDict to ensure proper order when saved to csv file
output_stats['total_duration'] = dict.fromkeys(
['1d', '1w', '1m', '1m_date', '1y'], 0)
output_stats['total_kwh'] = dict.fromkeys(
['1d', '1w', '1m', '1m_date', '1y'], 0)
output_stats['total_cost'] = dict.fromkeys(
['1d', '1w', '1m', '1m_date', '1y'], 0)
for each_output in table_outputs:
if ('output_types' in dict_outputs[each_output.output_type]
and 'on_off'
in dict_outputs[each_output.output_type]['output_types']
and each_output.amps):
past_1d_hours = output_sec_on(each_output.unique_id, 86400) / 3600
past_1w_hours = output_sec_on(each_output.unique_id, 604800) / 3600
past_1m_hours = output_sec_on(each_output.unique_id,
2629743) / 3600
past_1m_date_hours = output_sec_on(each_output.unique_id,
int(past_month_seconds)) / 3600
past_1y_hours = output_sec_on(each_output.unique_id,
31556926) / 3600
past_1d_kwh = table_misc.output_usage_volts * each_output.amps * past_1d_hours / 1000
past_1w_kwh = table_misc.output_usage_volts * each_output.amps * past_1w_hours / 1000
past_1m_kwh = table_misc.output_usage_volts * each_output.amps * past_1m_hours / 1000
past_1m_date_kwh = table_misc.output_usage_volts * each_output.amps * past_1m_date_hours / 1000
past_1y_kwh = table_misc.output_usage_volts * each_output.amps * past_1y_hours / 1000
output_stats[each_output.unique_id] = {
'1d': {
'hours_on': past_1d_hours,
'kwh': past_1d_kwh,
'cost': table_misc.output_usage_cost * past_1d_kwh
},
'1w': {
'hours_on': past_1w_hours,
'kwh': past_1w_kwh,
'cost': table_misc.output_usage_cost * past_1w_kwh
},
'1m': {
'hours_on': past_1m_hours,
'kwh': past_1m_kwh,
'cost': table_misc.output_usage_cost * past_1m_kwh
},
'1m_date': {
'hours_on': past_1m_date_hours,
'kwh': past_1m_date_kwh,
'cost': table_misc.output_usage_cost * past_1m_date_kwh
},
'1y': {
'hours_on': past_1y_hours,
'kwh': past_1y_kwh,
'cost': table_misc.output_usage_cost * past_1y_kwh
}
}
output_stats['total_duration']['1d'] += past_1d_hours
output_stats['total_duration']['1w'] += past_1w_hours
output_stats['total_duration']['1m'] += past_1m_hours
output_stats['total_duration']['1m_date'] += past_1m_date_hours
output_stats['total_duration']['1y'] += past_1y_hours
output_stats['total_kwh']['1d'] += past_1d_kwh
output_stats['total_kwh']['1w'] += past_1w_kwh
output_stats['total_kwh']['1m'] += past_1m_kwh
output_stats['total_kwh']['1m_date'] += past_1m_date_kwh
output_stats['total_kwh']['1y'] += past_1y_kwh
output_stats['total_cost'][
'1d'] += table_misc.output_usage_cost * past_1d_kwh
output_stats['total_cost'][
'1w'] += table_misc.output_usage_cost * past_1w_kwh
output_stats['total_cost'][
'1m'] += table_misc.output_usage_cost * past_1m_kwh
output_stats['total_cost'][
'1m_date'] += table_misc.output_usage_cost * past_1m_date_kwh
output_stats['total_cost'][
'1y'] += table_misc.output_usage_cost * past_1y_kwh
return output_stats
def return_output_usage(table_misc, table_outputs):
""" Return output usage and cost """
date_now = datetime.date.today()
time_now = datetime.datetime.now()
past_month_seconds = 0
if table_misc.output_usage_dayofmonth == datetime.datetime.today().day:
past_month_seconds = (time_now - time_now.replace(
hour=0, minute=0, second=0, microsecond=0)).total_seconds()
elif table_misc.output_usage_dayofmonth > datetime.datetime.today().day:
first_day = date_now.replace(day=1)
last_month = first_day - datetime.timedelta(days=1)
past_month = last_month.replace(day=table_misc.output_usage_dayofmonth)
past_month_seconds = (date_now - past_month).total_seconds()
elif table_misc.output_usage_dayofmonth < datetime.datetime.today().day:
past_month = date_now.replace(day=table_misc.output_usage_dayofmonth)
past_month_seconds = (date_now - past_month).total_seconds()
output_stats = OrderedDict()
for each_output in table_outputs:
if each_output.output_type != 'pwm':
output_stats[each_output.unique_id] = None
# Calculate output on duration for different time periods
# Use OrderedDict to ensure proper order when saved to csv file
output_stats['total_duration'] = dict.fromkeys(['1d', '1w', '1m', '1m_date', '1y'], 0)
output_stats['total_kwh'] = dict.fromkeys(['1d', '1w', '1m', '1m_date', '1y'], 0)
output_stats['total_cost'] = dict.fromkeys(['1d', '1w', '1m', '1m_date', '1y'], 0)
for each_output in table_outputs:
if each_output.output_type != 'pwm':
past_1d_hours = output_sec_on(each_output.unique_id, 86400) / 3600
past_1w_hours = output_sec_on(each_output.unique_id, 604800) / 3600
past_1m_hours = output_sec_on(each_output.unique_id, 2629743) / 3600
past_1m_date_hours = output_sec_on(each_output.unique_id, int(past_month_seconds)) / 3600
past_1y_hours = output_sec_on(each_output.unique_id, 31556926) / 3600
past_1d_kwh = table_misc.output_usage_volts * each_output.amps * past_1d_hours / 1000
past_1w_kwh = table_misc.output_usage_volts * each_output.amps * past_1w_hours / 1000
past_1m_kwh = table_misc.output_usage_volts * each_output.amps * past_1m_hours / 1000
past_1m_date_kwh = table_misc.output_usage_volts * each_output.amps * past_1m_date_hours / 1000
past_1y_kwh = table_misc.output_usage_volts * each_output.amps * past_1y_hours / 1000
output_stats[each_output.unique_id] = {
'1d': {
'hours_on': past_1d_hours,
'kwh': past_1d_kwh,
'cost': table_misc.output_usage_cost * past_1d_kwh
},
'1w': {
'hours_on': past_1w_hours,
'kwh': past_1w_kwh,
'cost': table_misc.output_usage_cost * past_1w_kwh
},
'1m': {
'hours_on': past_1m_hours,
'kwh': past_1m_kwh,
'cost': table_misc.output_usage_cost * past_1m_kwh
},
'1m_date': {
'hours_on': past_1m_date_hours,
'kwh': past_1m_date_kwh,
'cost': table_misc.output_usage_cost * past_1m_date_kwh
},
'1y': {
'hours_on': past_1y_hours,
'kwh': past_1y_kwh,
'cost': table_misc.output_usage_cost * past_1y_kwh
}
}
output_stats['total_duration']['1d'] += past_1d_hours
output_stats['total_duration']['1w'] += past_1w_hours
output_stats['total_duration']['1m'] += past_1m_hours
output_stats['total_duration']['1m_date'] += past_1m_date_hours
output_stats['total_duration']['1y'] += past_1y_hours
output_stats['total_kwh']['1d'] += past_1d_kwh
output_stats['total_kwh']['1w'] += past_1w_kwh
output_stats['total_kwh']['1m'] += past_1m_kwh
output_stats['total_kwh']['1m_date'] += past_1m_date_kwh
output_stats['total_kwh']['1y'] += past_1y_kwh
output_stats['total_cost']['1d'] += table_misc.output_usage_cost * past_1d_kwh
output_stats['total_cost']['1w'] += table_misc.output_usage_cost * past_1w_kwh
output_stats['total_cost']['1m'] += table_misc.output_usage_cost * past_1m_kwh
output_stats['total_cost']['1m_date'] += table_misc.output_usage_cost * past_1m_date_kwh
output_stats['total_cost']['1y'] += table_misc.output_usage_cost * past_1y_kwh
return output_stats