def test_cityreader_stretch_correctness(self):
     expected = [
         City("Albuquerque", 35.1055,-106.6476),
         City("Riverside", 33.9382,-117.3949),
         City("San Diego", 32.8312,-117.1225),
         City("Los Angeles", 34.114,-118.4068),
         City("Las Vegas", 36.2288,-115.2603),
         City("Denver", 39.7621,-104.8759),
         City("Phoenix", 33.5722,-112.0891),
         City("Tucson", 32.1558,-110.8777),
         City("Salt Lake City", 40.7774,-111.9301)
     ]
def city_reader_1(city = []):
    with open('cities.csv') as csv_file:
        csv_reader = csv.reader(csv_file, delimiter=',')
        line_count = 0

        for row in csv_reader:
            if line_count == 0:
                line_count += 1
            else:
                city.append(City(row[0], row[3], row[4]))
                line_count += 1
    return city
Пример #3
0
    def test_cityreader_stretch_correctness(self):
        expected = [
            City("Albuquerque", 35.1055, -106.6476),
            City("Riverside", 33.9382, -117.3949),
            City("San Diego", 32.8312, -117.1225),
            City("Los Angeles", 34.114, -118.4068),
            City("Las Vegas", 36.2288, -115.2603),
            City("Denver", 39.7621, -104.8759),
            City("Phoenix", 33.5722, -112.0891),
            City("Tucson", 32.1558, -110.8777),
            City("Salt Lake City", 40.7774, -111.9301)
        ]

        inp = cityreader_stretch(45, -100, 32, -120, self.cities)
        self.assertEqual(len(inp), len(expected))

        for i in range(len(inp)):
            self.assertTrue(check_city(inp[i], expected[i]))

        inp = cityreader_stretch(32, -120, 45, -100, self.cities)

        self.assertEqual(len(inp), len(expected))

        for i in range(len(inp)):
            self.assertTrue(check_city(inp[i], expected[i]))

        expected = [
            City("Richmond", 37.5294, -77.4755),
            City("Virginia Beach", 36.7335, -76.0435),
            City("Washington", 38.9047, -77.0163),
            City("Orlando", 28.4801, -81.3448),
            City("Miami", 25.784, -80.2102),
            City("Tampa", 27.9937, -82.4454),
            City("Jacksonville", 30.3322, -81.6749),
            City("Albuquerque", 35.1055, -106.6476),
            City("Fort Worth", 32.7813, -97.3466),
            City("McAllen", 26.2203, -98.2457),
            City("El Paso", 31.8478, -106.431),
            City("Dallas", 32.7938, -96.7659),
            City("Austin", 30.3038, -97.7545),
            City("Houston", 29.7871, -95.3936),
            City("San Antonio", 29.4722, -98.5247),
            City("New Orleans", 30.0687, -89.9288),
            City("Charlotte", 35.208, -80.8308),
            City("Raleigh", 35.8323, -78.6441),
            City("Memphis", 35.1047, -89.9773),
            City("Nashville", 36.1714, -86.7844),
            City("Riverside", 33.9382, -117.3949),
            City("San Diego", 32.8312, -117.1225),
            City("Los Angeles", 34.114, -118.4068),
            City("Las Vegas", 36.2288, -115.2603),
            City("Denver", 39.7621, -104.8759),
            City("Atlanta", 33.7627, -84.4231),
            City("Indianapolis", 39.7771, -86.1458),
            City("Oklahoma City", 35.4677, -97.5138),
            City("Phoenix", 33.5722, -112.0891),
            City("Tucson", 32.1558, -110.8777),
            City("Baltimore", 39.3051, -76.6144),
            City("Columbus", 39.9859, -82.9852),
            City("Cincinnati", 39.1412, -84.506),
            City("Saint Louis", 38.6358, -90.2451),
            City("Kansas City", 39.1239, -94.5541),
            City("Louisville", 38.1662, -85.6488)
        ]

        inp = cityreader_stretch(40, -50, 12, -120, self.cities)

        for i in range(len(inp)):
            self.assertTrue(check_city(inp[i], expected[i]))
 def setUp(self):
   self.cities = cityreader()
   self.expected = [
     City("Seattle", 47.6217,-122.3238),
     City("Richmond", 37.5294,-77.4755),
     City("Virginia Beach", 36.7335,-76.0435),
     City("Washington", 38.9047,-77.0163),
     City("Milwaukee", 43.064,-87.9669),
     City("Orlando", 28.4801,-81.3448),
     City("Miami", 25.784,-80.2102),
     City("Tampa", 27.9937,-82.4454),
     City("Jacksonville", 30.3322,-81.6749),
     City("Albuquerque", 35.1055,-106.6476),
     City("Fort Worth", 32.7813,-97.3466),
     City("McAllen", 26.2203,-98.2457),
     City("El Paso", 31.8478,-106.431),
     City("Dallas", 32.7938,-96.7659),
     City("Austin", 30.3038,-97.7545),
     City("Houston", 29.7871,-95.3936),
     City("San Antonio", 29.4722,-98.5247),
     City("New Orleans", 30.0687,-89.9288),
     City("Charlotte", 35.208,-80.8308),
     City("Raleigh", 35.8323,-78.6441),
     City("Omaha", 41.2634,-96.0453),
     City("Memphis", 35.1047,-89.9773),
     City("Nashville", 36.1714,-86.7844),
     City("Buffalo", 42.9016,-78.8487),
     City("Queens", 40.7498,-73.7976),
     City("New York", 40.6943,-73.9249),
     City("Bronx", 40.8501,-73.8662),
     City("Brooklyn", 40.6501,-73.9496),
     City("Manhattan", 40.7834,-73.9662),
     City("Philadelphia", 40.0076,-75.134),
     City("Pittsburgh", 40.4396,-79.9763),
     City("Sacramento", 38.5666,-121.4683),
     City("Riverside", 33.9382,-117.3949),
     City("San Francisco", 37.7561,-122.4429),
     City("San Diego", 32.8312,-117.1225),
     City("San Jose", 37.302,-121.8488),
     City("Los Angeles", 34.114,-118.4068),
     City("Las Vegas", 36.2288,-115.2603),
     City("Denver", 39.7621,-104.8759),
     City("Chicago", 41.8373,-87.6861),
     City("Atlanta", 33.7627,-84.4231),
     City("Indianapolis", 39.7771,-86.1458),
     City("Oklahoma City", 35.4677,-97.5138),
     City("Phoenix", 33.5722,-112.0891),
     City("Tucson", 32.1558,-110.8777),
     City("Bridgeport", 41.1909,-73.1958),
     City("Hartford", 41.7661,-72.6834),
     City("Baltimore", 39.3051,-76.6144),
     City("Boston", 42.3189,-71.0838),
     City("Cleveland", 41.4766,-81.6805),
     City("Columbus", 39.9859,-82.9852),
     City("Cincinnati", 39.1412,-84.506),
     City("Salt Lake City", 40.7774,-111.9301),
     City("Saint Louis", 38.6358,-90.2451),
     City("Kansas City", 39.1239,-94.5541),
     City("Minneapolis", 44.9635,-93.2679),
     City("Detroit", 42.3834,-83.1024),
     City("Providence", 41.8229,-71.4186),
     City("Louisville", 38.1662,-85.6488),
     City("Portland", 45.5372,-122.65)
   ]
import csv
from cityreader import City

# read the file
out = open('cities.csv', 'r')
data = csv.reader(out)
data = [row for row in data]
out.close()

# transfer data into a city objects and store in a list
cities = []
for x in range(1, len(data)):
    new_city = City(data[x][0], float(data[x][3]), float(data[x][4]))
    cities.append(new_city)
print(cities)
# Ensure that the lat and lon valuse are all floats
print(type(new_city.lat), type(new_city.lon))