def determine_estimate():
### Gets addresses, converts them to coordinates, requests estimates from API, creates dictionary, saves to a session to use later
uber_prices = []
app_start_address = request.args.get('start_address')
app_end_address = request.args.get('end_address')
### This is a fix for the problem that arose from the geocode lbirary, fixes SSL restrictions. See site for more details: https://urllib3.readthedocs.org/en/latest/security.html#pyopenssl
try:
import urllib3.contrib.pyopenssl
urllib3.contrib.pyopenssl.inject_into_urllib3()
except ImportError:
pass
### If the server receives correct input, it will convert to coordinates, make reuqest from Uber API, if not it will display an error message
try:
if Geocoder.geocode(app_start_address).valid_address and Geocoder.geocode(app_end_address).valid_address is True:
start_lat = Geocoder.geocode(app_start_address)[0].coordinates[0]
start_long = Geocoder.geocode(app_start_address)[0].coordinates[1]
end_lat = Geocoder.geocode(app_end_address)[0].coordinates[0]
end_long = Geocoder.geocode(app_end_address)[0].coordinates[1]
AUTH = Uber(ENV.CLIENT_ID, ENV.SERVER_TOKEN, ENV.SECRET)
estimate = AUTH.get_price_estimate(start_lat, start_long, end_lat, end_long)
services_and_prices = estimate['prices']
for i in range(len(services_and_prices)):
uber_price = {}
uber_price['service'] = services_and_prices[i]['display_name']
uber_price['price'] = services_and_prices[i]['estimate']
uber_prices.append(uber_price)
session['user_travel'] = uber_prices
return render_template("results.html")
else:
message = "Something went wrong. Please make sure you entered valid addresses."
return render_template("index.html", message=message)
except:
message = "Something went wrong. Please make sure you entered valid addresses."
return render_template("index.html", message=message)
def uber_json(xid,listings,id_rowidx,B):
xid=9062929
xrow=idrowidx[xid]
k=min(len(B)/10,20)
top20=B.sort(['review_scores_value'],ascending=False).index[0:k]
near=B.loc[top20]
doc_id=[i for i in near.index]
doc_id[-1]=xrow
tfidf=vect.fit_transform(list(listings['description'][doc_id]))
#print pd.DataFrame((tfidf * tfidf.T).A)[19]
arr = pd.DataFrame((tfidf * tfidf.T).A)[19]
argmax=arr.argsort()[-len(arr):][::-1]
similar_id={}
listings['uber']=0
uber = Uber('uHcGyypDvCoajjhhx-cyTdcnpZzbQV9j', 'V320Y_XH3wStYXbNGaqgoUV1dGX84eYfJfaCHNXS','GxoruYkFBi_kKaCYwYnILL_45UuVE729e5ohN7wW')
for x in argmax:
raw_row=doc_id[x]
lon=listings['longitude'][raw_row]
lat=listings['latitude'][raw_row]
end_lon =listings['longitude'][xrow]
end_lat =listings['latitude'][xrow]
fare_estimate = uber.get_price_estimate(lat,lon, end_lat,end_lon)
uberfare=fare_estimate['prices'][0]['low_estimate']*2
totalfare=listings['price'][raw_row]+uberfare
if totalfare<price:
similar_id[raw_row]=uberfare
print(raw_row)
listings['uber'][raw_row]=uberfare
if len(similar_id)==5:
break
sim_id=similar_id.keys()
temp=listings.loc[sim_id]
ttemp=temp[['id','longitude','latitude','name','summary','price','uber']]
dtemp= [
dict([
(colname, row[i])
for i,colname in enumerate(ttemp.columns)
])
for row in ttemp.values
]
return dtemp
def get_time_estimate(car_type):
product_id = None
for car in time_estimate:
if car['display_name'] == car_type:
product_id = car['product_id']
waiting_estimate = car['estimate']
break
return (product_id, waiting_estimate)
product_id, waiting_estimate = get_time_estimate(get_car_type())
end_latitude, end_longitude,output = get_loc()
print output
price_data = json.dumps(uber.get_price_estimate(start_latitude, start_longitude, end_latitude, end_longitude))
ride_data = json.loads(price_data)
all_rides = ride_data['prices']
for ride in all_rides:
if ride['product_id'] == product_id:
display_name = ride['display_name']
price_estimate = ride['high_estimate']
#s.write("Olin College\nNeedham&")
tmp = 0
for i in xrange(output.count(' ')):
tmp_old = tmp
tmp = output.find(' ', tmp+1);
if 12 < tmp < 17:
secret = '6YA8yP80GMtYbLYmZsY1oNI3fwlEEOObDiws-1-o'
uber = Uber(client_id, server_token, secret)
latitude = 51.5286416
longitude = -0.1015987
uber_products = uber.get_products(latitude, longitude)
# pprint.pprint(uber_products)
start_latitude = '28.53544'
start_longitude = '77.26393'
end_latitude = '28.45950'
end_longitude = '77.02664'
# uber.get_fare_estimate
# time_estimate = uber.get_time_estimate(start_latitude, start_longitude, customer_uuid=None, product_id=None)
fare_estimate = uber.get_price_estimate(start_latitude, start_longitude, end_latitude, end_longitude)
pprint.pprint(fare_estimate)
date = str(time.strftime('%y/%m/%d'))
price_go = [ fe['low_estimate'] for fe in fare_estimate['prices'] if fe['display_name']=='uberGO (Delhi to NCR)'][0]
# print price_go
price_x = [ fe['low_estimate'] for fe in fare_estimate['prices'] if fe['display_name']=='uberX (Within Delhi)'][0]
# for fe in fare_estimate['prices']:
# low_estimate = fe['low_estimate']
# display_name = fe['display_name']
# print low_estimate
# print display_name
# print date
# if display_name=='uberGO (Delhi to NCR)' or display_name=='uberX (Within Delhi)':
# Prints JSON object in a format that won't make you insane
print json.dumps(uber_products, sort_keys=True, indent=4, separators=(',', ': '))
### This is a fix for the problem that arose from the geocode lbirary, fixes SSL restrictions. See site for more details: https://urllib3.readthedocs.org/en/latest/security.html#pyopenssl
# try:
# import urllib3.contrib.pyopenssl
# urllib3.contrib.pyopenssl.inject_into_urllib3()
# except ImportError:
# pass
###
start_lat = Geocoder.geocode("180 Townsend Street, San Francisco, CA 94107")[0].coordinates[0]
start_long = Geocoder.geocode("180 Townsend Street, San Francisco, CA 94107")[0].coordinates[1]
end_lat = Geocoder.geocode("1737 Haight St, San Francisco, CA 94117")[0].coordinates[0]
end_long = Geocoder.geocode("1737 Haight St, San Francisco, CA 94117")[0].coordinates[1]
start_lat_test = Geocoder.geocode("poop").valid_address
print start_lat_test
estimate = AUTH.get_price_estimate(start_lat, start_long, end_lat, end_long)
print json.dumps(estimate, sort_keys=True, indent=4, separators=(',', ': '))
print estimate["prices"][0]["estimate"]
