def _query_api(self, api_query):
"""Uses PVWatts API to query for a PV profile."""
ssl_verify, proxy_settings = check_connection_settings()
try:
with requests.Session() as req:
http_request = req.get(api_query,
proxies=proxy_settings,
timeout=10,
verify=ssl_verify,
stream=True)
if http_request.status_code != requests.codes.ok:
http_request.raise_for_status()
except requests.HTTPError as e:
logging.error('PVProfileDM: {0}'.format(repr(e)))
raise requests.ConnectionError
except requests.exceptions.ProxyError:
logging.error('PVProfileDM: Could not connect to proxy.')
raise requests.ConnectionError
except requests.ConnectionError as e:
logging.error(
'PVProfileDM: Failed to establish a connection to the host server.'
)
raise requests.ConnectionError
except requests.Timeout as e:
logging.error('PVProfileDM: The connection timed out.')
raise requests.ConnectionError
except requests.RequestException as e:
logging.error('PVProfileDM: {0}'.format(repr(e)))
raise requests.ConnectionError
except Exception as e:
# Something else went wrong.
logging.error(
'PVProfileDM: An unexpected error has occurred. ({0})'.format(
repr(e)))
raise requests.ConnectionError
else:
request_content = http_request.json()
if not self.save_name_field.text:
popup = WarningPopup()
popup.popup_text.text = 'Please specify a name to save the PV profile as.'
popup.open()
return
else:
outname = self.save_name_field.text
# Strip non-alphanumeric chars from given name for filename.
delchars = ''.join(c for c in map(chr, range(256))
if not c.isalnum())
outname = outname.translate({ord(i): None for i in delchars})
# Save.
destination_dir = os.path.join(DATA_HOME, 'pv')
os.makedirs(destination_dir, exist_ok=True)
destination_file = os.path.join(destination_dir, outname + '.json')
if not os.path.exists(destination_file):
with open(destination_file, 'w') as outfile:
json.dump(request_content, outfile)
logging.info('PVProfileDM: Profile successfully saved.')
popup = WarningPopup()
popup.title = 'Success!'
popup.popup_text.text = 'PV profile successfully saved.'
popup.open()
else:
# File already exists with same name.
popup = WarningPopup()
popup.popup_text.text = 'A PV profile with the provided name already exists. Please specify a new name.'
popup.open()
finally:
self.save_button.disabled = False
def __init__(self, write_directory=None, write_function=None, chooser_description=None, format_description=None, data_validation_function=None, **kwargs):
super(DataImporter, self).__init__(**kwargs)
if write_directory is None:
self.write_directory = ""
else:
self.write_directory = write_directory
if write_function is None:
def _write_time_series_csv(fname, dataframe):
"""Writes a generic time series dataframe to a two-column csv.
The data is inferred to be at an hourly time resolution for one standard year.
Parameters
----------
fname : str
Name of the file to be saved without an extension
dataframe : Pandas DataFrame
DataFrame containing a single Series of the data
Returns
-------
str
The save destination of the resulting file.
"""
save_destination = os.path.join(self.write_directory, fname + ".csv")
data_column_name = dataframe.columns[0]
datetime_start = datetime(2019, 1, 1, 0)
hour_range = pd.date_range(start=datetime_start, periods=len(dataframe), freq="H")
dataframe["DateTime"] = hour_range
dataframe[["DateTime", data_column_name]].to_csv(save_destination, index=False)
return save_destination
self.write_function = _write_time_series_csv
else:
self.write_function = write_function
if chooser_description is None:
self.chooser_description = "Select a .csv file to import data from."
else:
self.chooser_description = chooser_description
file_chooser_screen = self.screen_manager.get_screen("FileChooser")
file_chooser_screen.file_chooser_body_text.text = self.chooser_description
if format_description is None:
self.format_description = "Specify the data column."
else:
self.format_description = format_description
format_analyzer_screen = self.screen_manager.get_screen("FormatAnalyzer")
format_analyzer_screen.format_analyzer_body_text.text = self.format_description
if data_validation_function is None:
def _default_data_validation_function(dataframe, data_column_name):
if len(dataframe) != 8760:
raise ValueError("The length of the time series must be 8760 (got {0}).".format(len(dataframe)))
data_column = dataframe[data_column_name]
try:
data_column.astype("float")
except ValueError:
raise ValueError("The selected data column could not be interpeted as numeric float values.")
self.data_validation_function = _default_data_validation_function
else:
self.data_validation_function = data_validation_function
# Bind DataImporter dismissal to successful data import.
completion_popup = WarningPopup()
completion_popup.title = "Success!"
completion_popup.popup_text.text = "Data successfully imported."
completion_popup.bind(on_dismiss=self.dismiss)
self.screen_manager.completion_popup = completion_popup
def save_load_data(self):
"""Saves the data for the building type selected."""
try:
csv_link = self._validate_selections()
except Exception as e:
print(e)
else:
ssl_verify, proxy_settings = check_connection_settings()
attempt_download = True
n_tries = 0
self.connection_error_occurred = False
while attempt_download:
n_tries += 1
if n_tries >= MAX_WHILE_ATTEMPTS:
logging.warning('LoadProfileDM: Hit download retry limit.')
attempt_download = False
self.connection_error_occurred = True
break
if App.get_running_app().root.stop.is_set():
return
try:
with requests.Session() as req:
page = req.get(csv_link,
timeout=10,
verify=ssl_verify,
proxies=proxy_settings)
if page.status_code != requests.codes.ok:
page.raise_for_status()
else:
attempt_download = False
except requests.HTTPError as e:
logging.error('LoadProfileDM: {0}'.format(repr(e)))
except requests.exceptions.ProxyError:
logging.error('LoadProfileDM: Could not connect to proxy.')
except requests.ConnectionError as e:
logging.error(
'LoadProfileDM: Failed to establish a connection to the host server.'
)
except requests.Timeout as e:
logging.error('LoadProfileDM: The connection timed out.')
except requests.RequestException as e:
logging.error('LoadProfileDM: {0}'.format(repr(e)))
except Exception as e:
# Something else went wrong.
logging.error(
'LoadProfileDM: An unexpected error has occurred. ({0})'
.format(repr(e)))
else:
data_down = page.content.decode(page.encoding)
csv_data = pd.read_csv(io.StringIO(data_down))
electricity_data = csv_data[[
'Date/Time', 'Electricity:Facility [kW](Hourly)'
]]
# Save to persistent object on disk.
url_split = csv_link.split('/')
destination_dir = os.path.join(DATA_HOME, 'load',
'residential',
url_split[-2])
os.makedirs(destination_dir, exist_ok=True)
destination_file = os.path.join(destination_dir,
url_split[-1])
electricity_data.to_csv(destination_file,
sep=',',
index=False)
popup = WarningPopup()
popup.title = 'Success!'
popup.popup_text.text = 'Load data successfully saved.'
popup.open()
logging.info(
'LoadProfileDM: Load data successfully saved.')
def save_rate_structure(self):
"""Saves the rate structure details to an object on disk."""
# Retrieve selections from other screens.
utility_search_screen = self.manager.get_screen('start')
utility_selected, rate_structure_selected = utility_search_screen.get_selections(
)
energy_rate_screen = self.manager.get_screen('energy_rate_structure')
energy_weekday_schedule, energy_weekend_schedule, energy_rates_dict = energy_rate_screen.get_selections(
)
demand_rate_screen = self.manager.get_screen('demand_rate_structure')
demand_weekday_schedule, demand_weekend_schedule, demand_tou_rates_dict, demand_flat_rates_dict = demand_rate_screen.get_selections(
)
try:
peak_kw_min, peak_kw_max, net_metering_type, sell_price = self.get_selections(
)
except TypeError:
return
# Form dictionary object for saving.
rate_structure_object = {}
if not self.save_name_field.text:
popup = WarningPopup()
popup.popup_text.text = 'Please specify a name to save the rate structure as.'
popup.open()
return
else:
rate_structure_object['name'] = self.save_name_field.text
rate_structure_object['utility'] = {
'utility name': utility_selected['utility_name'],
'rate structure name': rate_structure_selected['name']
}
rate_structure_object['energy rate structure'] = {
'weekday schedule': energy_weekday_schedule,
'weekend schedule': energy_weekend_schedule,
'energy rates': energy_rates_dict
}
rate_structure_object['demand rate structure'] = {
'weekday schedule': demand_weekday_schedule,
'weekend schedule': demand_weekend_schedule,
'time of use rates': demand_tou_rates_dict,
'flat rates': demand_flat_rates_dict,
'minimum peak demand': peak_kw_min,
'maximum peak demand': peak_kw_max
}
rate_structure_object['net metering'] = {
'type': net_metering_type,
'energy sell price': sell_price
}
# Save to JSON.
# Strip non-alphanumeric chars from given name for filename.
delchars = ''.join(c for c in map(chr, range(256)) if not c.isalnum())
fname = rate_structure_object['name'].translate(
{ord(i): None
for i in delchars})
destination_dir = os.path.join(DATA_HOME, 'rate_structures')
os.makedirs(destination_dir, exist_ok=True)
destination_file = os.path.join(destination_dir, fname + '.json')
if not os.path.exists(destination_file):
with open(destination_file, 'w') as outfile:
json.dump(rate_structure_object, outfile)
popup = WarningPopup()
popup.title = 'Success!'
popup.popup_text.text = 'Rate structure data successfully saved.'
popup.open()
else:
# File already exists with same name.
popup = WarningPopup()
popup.popup_text.text = 'A rate structure with the provided name already exists. Please specify a new name.'
popup.open()