def test_broken(self):
exception = False
try:
clear_mappers()
dao = Dao("")
dao.load_gtfs(BROKEN_GTFS, lenient=False)
except KeyError:
exception = True
self.assertTrue(exception)
clear_mappers()
dao = Dao("")
dao.load_gtfs(BROKEN_GTFS, lenient=True)
# The following are based on BROKEN GTFS content,
# that is the entities count minus broken ones.
self.assertTrue(len(dao.routes()) == 4)
self.assertTrue(len(list(dao.stops())) == 12)
self.assertTrue(len(dao.calendars()) == 2)
self.assertTrue(len(list(dao.trips())) == 104)
self.assertTrue(len(dao.stoptimes()) == 500)
self.assertTrue(len(dao.fare_attributes()) == 2)
self.assertTrue(len(dao.fare_rules()) == 4)
# This stop has missing coordinates in the broken file
stop00 = dao.stop('FUR_CREEK_RES3')
self.assertAlmostEquals(stop00.stop_lat, 0.0, 5)
self.assertAlmostEquals(stop00.stop_lon, 0.0, 5)
def test_broken(self):
exception = False
try:
dao = Dao("")
dao.load_gtfs(BROKEN_GTFS, lenient=False)
except KeyError:
exception = True
self.assertTrue(exception)
dao = Dao("")
dao.load_gtfs(BROKEN_GTFS, lenient=True)
# The following are based on BROKEN GTFS content,
# that is the entities count minus broken ones.
self.assertTrue(len(dao.routes()) == 4)
self.assertTrue(len(list(dao.stops())) == 12)
self.assertTrue(len(dao.calendars()) == 2)
self.assertTrue(len(list(dao.trips())) == 104)
self.assertTrue(len(dao.stoptimes()) == 500)
self.assertTrue(len(dao.fare_attributes()) == 2)
self.assertTrue(len(dao.fare_rules()) == 4)
# This stop has missing coordinates in the broken file
stop00 = dao.stop('FUR_CREEK_RES3')
self.assertAlmostEquals(stop00.stop_lat, 0.0, 5)
self.assertAlmostEquals(stop00.stop_lon, 0.0, 5)
def test_complex_queries(self):
dao = Dao(DAO_URL, sql_logging=SQL_LOG)
dao.load_gtfs(DUMMY_GTFS)
# Get the list of departures:
# 1) from "Porte de Bourgogne"
# 2) on 4th July
# 3) between 10:00 and 14:00
# 4) on route type BUS
# 5) not the last of trip (only departing)
porte_bourgogne = dao.stop("BBG")
july4 = CalendarDate.ymd(2016, 7, 4)
from_time = gtfstime(10, 00)
to_time = gtfstime(14, 00)
departures = dao.stoptimes(
fltr=(StopTime.stop == porte_bourgogne) & (StopTime.departure_time >= from_time) & (StopTime.departure_time <= to_time)
& (Route.route_type == Route.TYPE_BUS) & (func.date(CalendarDate.date) == july4.date),
prefetch_trips=True)
n = 0
for dep in departures:
self.assertTrue(dep.stop == porte_bourgogne)
self.assertTrue(july4 in dep.trip.calendar.dates)
self.assertTrue(dep.trip.route.route_type == Route.TYPE_BUS)
self.assertTrue(dep.departure_time >= from_time and dep.departure_time <= to_time)
n += 1
self.assertTrue(n > 10)
# Plage is a stop that is used only in summer (hence the name!)
plage = dao.stop("BPG")
# Get the list of stops used by some route:
# 1) All-year round
route_red = dao.route("BR")
stoplist_all = list(dao.stops(fltr=Trip.route == route_red))
# 2) Only in january
from_date = CalendarDate.ymd(2016, 1, 1)
to_date = CalendarDate.ymd(2016, 1, 31)
stoplist_jan = list(dao.stops(
fltr=(Trip.route == route_red) & (func.date(CalendarDate.date) >= from_date.date) & (func.date(CalendarDate.date) <= to_date.date)))
# Now, make some tests
self.assertTrue(len(stoplist_all) > 5)
self.assertTrue(plage in stoplist_all)
self.assertFalse(plage in stoplist_jan)
stoplist = list(stoplist_all)
stoplist.remove(plage)
self.assertTrue(set(stoplist) == set(stoplist_jan))
# Get all routes passing by the set of stops
routes = dao.routes(fltr=or_(StopTime.stop == stop for stop in stoplist_jan))
stopset = set()
for route in routes:
for trip in route.trips:
for stoptime in trip.stop_times:
stopset.add(stoptime.stop)
self.assertTrue(set(stoplist_jan).issubset(stopset))
def test_demo(self):
dao = Dao(DAO_URL, sql_logging=False)
dao.load_gtfs(DUMMY_GTFS)
print("List of stops named '...Bordeaux...':")
stops_bordeaux = list(dao.stops(fltr=(Stop.stop_name.ilike('%Bordeaux%')) & (Stop.location_type == Stop.TYPE_STOP)))
for stop in stops_bordeaux:
print(stop.stop_name)
print("List of routes passing by those stops:")
routes_bordeaux = dao.routes(fltr=or_(StopTime.stop == stop for stop in stops_bordeaux))
for route in routes_bordeaux:
print("%s - %s" % (route.route_short_name, route.route_long_name))
july4 = CalendarDate.ymd(2016, 7, 4)
print("All departures from those stops on %s:" % (july4.as_date()))
departures = list(dao.stoptimes(fltr=(or_(StopTime.stop == stop for stop in stops_bordeaux)) & (StopTime.departure_time != None) & (func.date(CalendarDate.date) == july4.date)))
print("There is %d departures" % (len(departures)))
for departure in departures:
print("%30.30s %10.10s %-20.20s > %s" % (departure.stop.stop_name, fmttime(departure.departure_time), departure.trip.route.route_long_name, departure.trip.trip_headsign))
print("Number of departures and time range per stop on %s:" % (july4.as_date()))
departure_by_stop = defaultdict(list)
for departure in departures:
departure_by_stop[departure.stop].append(departure)
for stop, deps in departure_by_stop.items():
min_dep = min(d.departure_time for d in deps)
max_dep = max(d.departure_time for d in deps)
print("%30.30s %3d departures (from %s to %s)" % (stop.stop_name, len(deps), fmttime(min_dep), fmttime(max_dep)))
# Compute the average distance and time to next stop by route type
ntd = [ [0, 0, 0.0] for type in range(0, Route.TYPE_FUNICULAR + 1) ]
for departure in departures:
# The following is guaranteed to succeed as we have departure_time == Null for last stop time in trip
next_arrival = departure.trip.stop_times[departure.stop_sequence + 1]
hop_dist = next_arrival.shape_dist_traveled - departure.shape_dist_traveled
hop_time = next_arrival.arrival_time - departure.departure_time
route_type = departure.trip.route.route_type
ntd[route_type][0] += 1
ntd[route_type][1] += hop_time
ntd[route_type][2] += hop_dist
for route_type in range(0, len(ntd)):
n, t, d = ntd[route_type]
if n > 0:
print("The average distance to the next stop on those departures for route type %d is %.2f meters" % (route_type, d / n))
print("The average time in sec to the next stop on those departures for route type %d is %s" % (route_type, fmttime(t / n)))
def test_demo(self):
dao = Dao(DAO_URL, sql_logging=False)
dao.load_gtfs(DUMMY_GTFS)
print("List of stops named '...Bordeaux...':")
stops_bordeaux = list(
dao.stops(fltr=(Stop.stop_name.ilike('%Bordeaux%'))
& (Stop.location_type == Stop.TYPE_STOP)))
for stop in stops_bordeaux:
print(stop.stop_name)
print("List of routes passing by those stops:")
routes_bordeaux = dao.routes(fltr=or_(StopTime.stop == stop
for stop in stops_bordeaux))
for route in routes_bordeaux:
print("%s - %s" % (route.route_short_name, route.route_long_name))
july4 = CalendarDate.ymd(2016, 7, 4)
print("All departures from those stops on %s:" % (july4.as_date()))
departures = list(
dao.stoptimes(fltr=(or_(StopTime.stop == stop
for stop in stops_bordeaux))
& (StopTime.departure_time != None)
& (func.date(CalendarDate.date) == july4.date)))
print("There is %d departures" % (len(departures)))
for departure in departures:
print("%30.30s %10.10s %-20.20s > %s" %
(departure.stop.stop_name, fmttime(departure.departure_time),
departure.trip.route.route_long_name,
departure.trip.trip_headsign))
print("Number of departures and time range per stop on %s:" %
(july4.as_date()))
departure_by_stop = defaultdict(list)
for departure in departures:
departure_by_stop[departure.stop].append(departure)
for stop, deps in departure_by_stop.items():
min_dep = min(d.departure_time for d in deps)
max_dep = max(d.departure_time for d in deps)
print("%30.30s %3d departures (from %s to %s)" %
(stop.stop_name, len(deps), fmttime(min_dep),
fmttime(max_dep)))
# Compute the average distance and time to next stop by route type
ntd = [[0, 0, 0.0] for type in range(0, Route.TYPE_FUNICULAR + 1)]
for departure in departures:
# The following is guaranteed to succeed as we have departure_time == Null for last stop time in trip
next_arrival = departure.trip.stop_times[departure.stop_sequence +
1]
hop_dist = next_arrival.shape_dist_traveled - departure.shape_dist_traveled
hop_time = next_arrival.arrival_time - departure.departure_time
route_type = departure.trip.route.route_type
ntd[route_type][0] += 1
ntd[route_type][1] += hop_time
ntd[route_type][2] += hop_dist
for route_type in range(0, len(ntd)):
n, t, d = ntd[route_type]
if n > 0:
print(
"The average distance to the next stop on those departures for route type %d is %.2f meters"
% (route_type, d / n))
print(
"The average time in sec to the next stop on those departures for route type %d is %s"
% (route_type, fmttime(t / n)))
