def _execute_search():
# Open loading screen.
# self.loading_screen = LoadingModalView()
# self.loading_screen.loading_text.text = 'Retrieving rate structures...'
# self.loading_screen.open()
if self.utility_ref_table.empty:
try:
self._download_utility_ref_table()
except requests.ConnectionError:
popup = ConnectionErrorPopup()
popup.popup_text.text = 'There was an issue connecting to and downloading the lists of utilities. Check your connection settings and try again.'
popup.open()
return
finally:
self.search_button.disabled = False
# Filter DataFrame by search type/query and drop duplicate entries.
if search_type == 'state':
utility_data_filtered = self.utility_ref_table.loc[
self.utility_ref_table['state'].str.lower(
).str.contains(search_query)
| self.utility_ref_table['state name'].str.lower(
).str.contains(search_query)]
elif search_type == 'zip':
utility_data_filtered = self.utility_ref_table.loc[
self.utility_ref_table[search_type] == search_query]
else:
utility_data_filtered = self.utility_ref_table.loc[
self.utility_ref_table[search_type].str.lower(
).str.contains(search_query)]
utility_data_filtered = utility_data_filtered[[
'eiaid', 'utility_name', 'state', 'ownership'
]]
utility_data_filtered.drop_duplicates(inplace=True)
logging.info(
'RateStructureDM: Utility table filter completed.')
self.search_button.disabled = False
if utility_data_filtered.empty:
logging.warning(
'RateStructureDM: No results matched the query.')
popup = WarningPopup()
popup.popup_text.text = 'No results matched your query.'
popup.open()
# Enable search results selector.
fade_in_animation(self.utility_select_bx)
self._populate_utility_selector(utility_data_filtered)
def _query_api_for_rate_structures(self, api_query):
"""Uses OpenEI API to query the rate structures for given EIA ID and populates rate structure RecycleView."""
ssl_verify, proxy_settings = check_connection_settings()
attempt_download = True
n_tries = 0
while attempt_download:
n_tries += 1
if n_tries >= MAX_WHILE_ATTEMPTS:
logging.warning('RateStructureDM: Hit download retry limit.')
attempt_download = False
break
if App.get_running_app().root.stop.is_set():
return
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()
else:
attempt_download = False
except requests.HTTPError as e:
logging.error('RateStructureDM: {0}'.format(repr(e)))
raise requests.ConnectionError
except requests.exceptions.ProxyError:
logging.error('RateStructureDM: Could not connect to proxy.')
raise requests.ConnectionError
except requests.ConnectionError as e:
logging.error(
'RateStructureDM: Failed to establish a connection to the host server.'
)
raise requests.ConnectionError
except requests.Timeout as e:
logging.error('RateStructureDM: The connection timed out.')
raise requests.ConnectionError
except requests.RequestException as e:
logging.error('RateStructureDM: {0}'.format(repr(e)))
raise requests.ConnectionError
except Exception as e:
# Something else went wrong.
logging.error(
'RateStructureDM: An unexpected error has occurred. ({0})'.
format(repr(e)))
raise requests.ConnectionError
else:
structure_list = http_request.json()['items']
structure_df = pd.DataFrame.from_records(structure_list)
structure_df.dropna(subset=['energyratestructure'],
inplace=True)
# Filter out entries whose energyratestructure array does not contain "rate" terms.
mask = structure_df['energyratestructure'].apply(lambda x: all(
['rate' in hr.keys() for row in x for hr in row]))
structure_df = structure_df[mask]
structure_list = structure_df.to_dict(orient='records')
# First, sort by effective date.
# structure_list = sorted(structure_list, key=lambda x: (x['name'], x.get('startdate', np.nan)))
structure_list = sorted(
structure_list,
key=lambda x: x.get('startdate', np.nan),
reverse=True)
# Then, sort by name.
structure_list = sorted(structure_list,
key=lambda x: x['name'])
# Display name: Name (record['startdate']).
effective_dates = [
'(Effective Date : {0})'.format(
dt.datetime.fromtimestamp(
record['startdate']).strftime('%m/%d/%Y'))
if not np.isnan(record['startdate']) else ''
for record in structure_list
]
records = [{
'name': record['name'] + ' ' + effective_dates[ix],
'record': record
} for ix, record in enumerate(structure_list, start=0)]
# records = sorted(records, key=lambda t: t['name'])
self.rate_structure_rv.data = records
self.rate_structure_rv.unfiltered_data = records
logging.info(
'RateStructureDM: Retrieved utility rate structures.')
fade_in_animation(self.rate_structure_select_bx)
finally:
self.loading_screen.dismiss()