def index():
config_file = os.path.join(os.path.dirname(__file__), 'config.json')
with open(config_file, 'r') as configFile:
config_dict = json.loads(configFile.read())
r = requests.get(config_dict['target_url'],
auth=HTTPBasicAuth(config_dict['client_id'],
config_dict['client_secret']))
parser = etree.XMLParser(recover=True)
d = pq(etree.fromstring(r.text, parser))
elements = [e.attrib['title'] for e in d("label.screen-name")]
credential_file = os.path.join(os.path.dirname(__file__),
'credential.json')
with open(credential_file, 'r') as dataFile:
credential_dict = json.loads(dataFile.read())
credentials = ServiceAccountCredentials.from_json_keyfile_dict(
credential_dict, scopes=['https://spreadsheets.google.com/feeds'])
gs_client = gspread.authorize(credentials)
gfile = gs_client.open_by_key(config_dict['doc_key'])
worksheet = gfile.sheet1
records = worksheet.get_all_values()
results = []
for i, r in enumerate(records):
if i > 0:
working = False
in_use = False
if r[3] != '':
in_use = True
for e in elements:
if r[0] in e:
working = True
result = {
'id': r[0],
'working': working,
'in_use': in_use,
'notifications': r[3],
'location': r[2]
}
results.append(result)
if in_use is False:
logging.info(u'{} is not in use, skipped'.format(r[0]))
continue
state = States.get_by_id(r[0])
if working is False:
if state is None or state.working is True:
logging.info(
u'{}: looks bad, notification task will be sent to que'
.format(r[0]))
States(id=r[0], working=False).put()
deferred.defer(send_notification, result)
else:
logging.info(
u'{}: looks bad, same status as before'.format(r[0]))
else:
logging.info(u'{}: looks good'.format(r[0]))
States(id=r[0], working=True).put()
return render_template('index.html', results=results)
def __init__(self,
Data,
lstm_neurons,
epochs,
ax,
gradient=0.9056,
dense_neruons=3):
self.lstm = LSTM(lstm_neurons, dense_neruons)
self.lstm.create_model()
self.lstm.fit_model(epochs, Data)
self.lstm.print_stats()
self.states = States(4000, 23000)
self.states.create_unperturbed(self.lstm, Data)
self.states.create_perturbed(self.lstm, Data)
self.Lyapunov = Lyapunov(self.states)
self.Lyapunov.plot_exponent(ax, gradient)
def state_abb():
""" seed states abbreviations into the database """
res = requests.get(STATES_API)
resp = res.json()
length = len(resp)
for y in range(0, length):
states_abb = resp[y]['state']
state_fips = resp[y]['fips']
state = States(state=state_fips, state_abb=states_abb)
db.session.add(state)
db.session.commit()
def add_statistics():
try:
for data in request.json['country_statistics']:
country = data['country']
code = data['code']
flag = data['flag']
coordinates = data['coordinates']
confirmed = data['confirmed']
deaths = data['deaths']
recovered = data['recovered']
all_states = []
for state in data['states']:
states = States(key=state['key'],
name=state['name'],
address=state['address'],
latitude=state['latitude'],
longitude=state['longitude'],
confirmed=state['confirmed'],
deaths=state['deaths'],
recovered=state['recovered'])
states.save()
all_states.append(states)
statistics = Statistics(country=country,
code=code,
flag=flag,
coordinates=coordinates,
confirmed=confirmed,
deaths=deaths,
recovered=recovered,
states=all_states)
statistics.save()
return make_response(jsonify({"success": request.json}), 201)
except KeyError:
abort(400)
def state_fc():
chatid = request.json['chat_id']
stage = request.json['stage']
ratee_email = request.json['ratee_email']
course_code = request.json['course_code']
skills = request.json['skills']
rater_email = request.json['rater_email']
valid_chatid = States.query.filter_by(chatid=chatid).first()
if valid_chatid is None:
new_entry = States(chatid=chatid,stage=stage,ratee_email1=ratee_email,course_code1=course_code,rate_skill1=skills,rater_email1=rater_email)
db.session.add(new_entry)
db.session.commit()
return(jsonify('{} has been entered'.format(chatid)),200)
init_db()
states_abbr = [
'al', 'ak', 'az', 'ar', 'ca', 'co', 'ct', 'dc', 'de', 'fl', 'ga', 'hi',
'id', 'il', 'in', 'ia', 'ks', 'ky', 'la', 'me', 'md', 'ma', 'mi', 'mn',
'ms', 'mo', 'mt', 'ne', 'nv', 'nh', 'nj', 'nm', 'ny', 'nc', 'nd', 'oh',
'ok', 'or', 'pa', 'ri', 'sc', 'sd', 'tn', 'tx', 'ut', 'vt', 'va', 'wa',
'wv', 'wi', 'wy'
]
df = pd.read_csv('national_parks.csv', encoding='latin-1')
df.drop_duplicates(subset='Name', inplace=True)
df = df.reset_index()
for state in states_abbr:
new_states = States(Name=state.upper())
for j in range(len(df)):
if state.upper() in df['Challenge State'][j]:
check_park = session.query(National_parks).filter_by(
Name=df['Name'][j]).first()
if check_park:
check_park.state.append(new_states)
else:
new_parks = National_parks(
Name=df['Name'][j],
Type=df['Type'][j],
Location=df['Location'][j],
Description=df['Description'][j],
Challenge_states=df['Challenge State'][j],