def collect_uber_data():
total_estimates = []
estimates = {}
#Global Learning Center GA TECH: 33.7762° N, 84.3895° W
for place in places:
estimates = {}
response = client.get_price_estimates(
start_latitude=33.7762,
start_longitude=-84.3895,
end_latitude=place["location"][0],
end_longitude=place["location"][1])
estimate = response.json.get('prices')
#print(estimate)
#estimate10
estimates["place"] = place["name"]
estimates["geometry"] = place["location"]
autotimeinit = datetime.now()
autotime = autotimeinit.strftime('%H:%M')
estimates["autotime"] = autotime
autohour = autotimeinit.strftime('%H')
autohour = autohour + ":00"
estimates["time"] = autohour
estimates["value"] = estimate
autoday = autotimeinit.strftime('%A')
estimates["day"] = autoday
estimates["value"] = estimate
# last_hour_date_time = datetime.now() - timedelta(hours = 1)
# list_datetime_capture.append(last_hour_date_time.strftime('%Y-%m-%d %H:%M:%S'))
total_estimates.append(estimates)
# print(len(total_estimates))
engine1 = create_engine('sqlite:///UberPricesNew.sqlite')
session1 = Session(engine1)
# Note that adding to the session does not update the table. It queues up those queries.
for values in total_estimates:
for value in values["value"]:
session1.add(
UberPricesNew(place=values["place"],
lat=values["geometry"][0],
lon=values["geometry"][1],
dist=value["distance"],
display_name=value["display_name"],
duration=value["duration"],
estimate=value["estimate"],
high_estimate=value["high_estimate"],
low_estimate=value["low_estimate"],
autotime=values["autotime"],
time=values["time"],
day=values["day"],
company="Uber"))
# commit() flushes whatever remaining changes remain to the database, and commits the transaction.
# print("uber done")
session1.commit()
# last_hour_date_time = datetime.now() - timedelta(hours = 1)
# list_datetime_capture.append(last_hour_date_time.strftime('%Y-%m-%d %H:%M:%S'))
lyft_total_estimates.append(estimates)
# lyft_total_estimates
print(len(lyft_total_estimates))
# Create our database engine
engine = create_engine('sqlite:///LyftPricesNew.sqlite')
# Base.metadata.create_all(engine)
# The ORM’s “handle” to the database is the Session.
from sqlalchemy.orm import Session
session = Session(engine)
# Note that adding to the session does not update the table. It queues up those queries.
for values in lyft_total_estimates:
for value in values["value"]:
session.add(LyftPricesNew(place=values["place"], lat=values["geometry"][0], lon=values["geometry"][1],
dist=value["estimated_distance_miles"], display_name = value["display_name"],
duration = value["estimated_duration_seconds"],
estimate = str(value["estimated_cost_cents_min"]//100) + " - " +str(value["estimated_cost_cents_max"]//100),
high_estimate = value["estimated_cost_cents_max"]//100,
low_estimate = value["estimated_cost_cents_min"]//100,
autotime=values["autotime"], time=values["time"]
))
# commit() flushes whatever remaining changes remain to the database, and commits the transaction.
session.commit()
time.sleep(60)
def collect_lyft_data():
lyft_total_estimates = []
estimates = {}
#Global Learning Center GA TECH: 33.7762° N, 84.3895° W
for place in places:
estimates = {}
url = "https://api.lyft.com/v1/cost?start_lat=33.7762&start_lng=-84.3895&end_lat=" + str(
place["location"][0]) + "&end_lng=" + str(place["location"][1])
# requests.get(url).json()
estimate = requests.get(url).json()["cost_estimates"]
#print(estimate)
#estimate10
estimates["place"] = place["name"]
estimates["geometry"] = place["location"]
autotimeinit = datetime.now()
autotime = autotimeinit.strftime('%H:%M')
estimates["autotime"] = autotime
autohour = autotimeinit.strftime('%H')
autohour = autohour + ":00"
estimates["time"] = autohour
autoday = autotimeinit.strftime('%A')
estimates["day"] = autoday
estimates["value"] = estimate
# last_hour_date_time = datetime.now() - timedelta(hours = 1)
# list_datetime_capture.append(last_hour_date_time.strftime('%Y-%m-%d %H:%M:%S'))
lyft_total_estimates.append(estimates)
# lyft_total_estimates
# print(len(lyft_total_estimates))
# Create our database engine
engine = create_engine('sqlite:///LyftPricesNew.sqlite')
# Base.metadata.create_all(engine)
# The ORM’s “handle” to the database is the Session.
session = Session(engine)
# Note that adding to the session does not update the table. It queues up those queries.
for values in lyft_total_estimates:
for value in values["value"]:
session.add(
LyftPricesNew(
place=values["place"],
lat=values["geometry"][0],
lon=values["geometry"][1],
dist=value["estimated_distance_miles"],
display_name=value["display_name"],
duration=value["estimated_duration_seconds"],
estimate=str(value["estimated_cost_cents_min"] // 100) +
" - " + str(value["estimated_cost_cents_max"] // 100),
high_estimate=value["estimated_cost_cents_max"] // 100,
low_estimate=value["estimated_cost_cents_min"] // 100,
autotime=values["autotime"],
time=values["time"],
day=values["day"],
company="Lyft"))
# commit() flushes whatever remaining changes remain to the database, and commits the transaction.
# print("lyft done")
session.commit()
