/usr/lib/python2.7/dist-packages/ephem/cities.py is in python-ephem 3.7.6.0-7build1.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 | """Modest database of more than a hundred world cities."""
import ephem
import json
import sys
from math import radians
_python3 = sys.version_info > (3,)
if _python3:
from urllib.parse import urlencode
from urllib.request import urlopen
else:
from urllib import urlencode
from urllib2 import urlopen
_city_data = {
'London': ('51.5001524', '-0.1262362', 14.605533), # United Kingdom
'Paris': ('48.8566667', '2.3509871', 35.917042), # France
'New York': ('40.7143528', '-74.0059731', 9.775694), # United States
'Tokyo': ('35.6894875', '139.6917064', 37.145370), # Japan
'Chicago': ('41.8781136', '-87.6297982', 181.319290), # United States
'Frankfurt': ('50.1115118', '8.6805059', 106.258285), # Germany
'Hong Kong': ('22.396428', '114.109497', 321.110260), # Hong Kong
'Los Angeles': ('34.0522342', '-118.2436849', 86.847092), # United States
'Milan': ('45.4636889', '9.1881408', 122.246513), # Italy
'Singapore': ('1.352083', '103.819836', 57.821636), # Singapore
'San Francisco': ('37.7749295', '-122.4194155', 15.557819), # United States
'Sydney': ('-33.8599722', '151.2111111', 3.341026), # Australia
'Toronto': ('43.6525', '-79.3816667', 90.239403), # Canada
'Zurich': ('47.3833333', '8.5333333', 405.500916), # Switzerland
'Brussels': ('50.8503', '4.35171', 26.808620), # Belgium
'Madrid': ('40.4166909', '-3.7003454', 653.005005), # Spain
'Mexico City': ('19.4270499', '-99.1275711', 2228.146484), # Mexico
'Sao Paulo': ('-23.5489433', '-46.6388182', 760.344849), # Brazil
'Moscow': ('55.755786', '37.617633', 151.189835), # Russian Federation
'Seoul': ('37.566535', '126.9779692', 41.980915), # South Korea
'Amsterdam': ('52.3730556', '4.8922222', 14.975505), # The Netherlands
'Boston': ('42.3584308', '-71.0597732', 15.338848), # United States
'Caracas': ('10.491016', '-66.902061', 974.727417), # Venezuela
'Dallas': ('32.802955', '-96.769923', 154.140625), # United States
'Dusseldorf': ('51.2249429', '6.7756524', 43.204800), # Germany
'Geneva': ('46.2057645', '6.141593', 379.026245), # Switzerland
'Houston': ('29.7628844', '-95.3830615', 6.916622), # United States
'Jakarta': ('-6.211544', '106.845172', 10.218226), # Indonesia
'Johannesburg': ('-26.1704415', '27.9717606', 1687.251099), # South Africa
'Melbourne': ('-37.8131869', '144.9629796', 27.000000), # Australia
'Osaka': ('34.6937378', '135.5021651', 16.347811), # Japan
'Prague': ('50.0878114', '14.4204598', 191.103485), # Czech Republic
'Santiago': ('-33.4253598', '-70.5664659', 665.926880), # Chile
'Taipei': ('25.091075', '121.5598345', 32.288563), # Taiwan
'Washington': ('38.8951118', '-77.0363658', 7.119641), # United States
'Bangkok': ('13.7234186', '100.4762319', 4.090096), # Thailand
'Beijing': ('39.904214', '116.407413', 51.858883), # China
'Montreal': ('45.5088889', '-73.5541667', 16.620916), # Canada
'Rome': ('41.8954656', '12.4823243', 19.704413), # Italy
'Stockholm': ('59.3327881', '18.0644881', 25.595907), # Sweden
'Warsaw': ('52.2296756', '21.0122287', 115.027786), # Poland
'Atlanta': ('33.7489954', '-84.3879824', 319.949738), # United States
'Barcelona': ('41.387917', '2.1699187', 19.991053), # Spain
'Berlin': ('52.5234051', '13.4113999', 45.013939), # Germany
'Buenos Aires': ('-34.6084175', '-58.3731613', 40.544090), # Argentina
'Budapest': ('47.4984056', '19.0407578', 106.463295), # Hungary
'Copenhagen': ('55.693403', '12.583046', 6.726723), # Denmark
'Hamburg': ('53.5538148', '9.9915752', 5.104634), # Germany
'Istanbul': ('41.00527', '28.97696', 37.314278), # Turkey
'Kuala Lumpur': ('3.139003', '101.686855', 52.271698), # Malaysia
'Manila': ('14.5833333', '120.9666667', 3.041384), # Philippines
'Miami': ('25.7889689', '-80.2264393', 0.946764), # United States
'Minneapolis': ('44.9799654', '-93.2638361', 253.002655), # United States
'Munich': ('48.1391265', '11.5801863', 523.000000), # Germany
'Shanghai': ('31.230393', '121.473704', 15.904707), # China
'Athens': ('37.97918', '23.716647', 47.597061), # Greece
'Auckland': ('-36.8484597', '174.7633315', 21.000000), # New Zealand
'Dublin': ('53.344104', '-6.2674937', 8.214323), # Ireland
'Helsinki': ('60.1698125', '24.9382401', 7.153307), # Finland
'Luxembourg': ('49.815273', '6.129583', 305.747925), # Luxembourg
'Lyon': ('45.767299', '4.8343287', 182.810547), # France
'Mumbai': ('19.0176147', '72.8561644', 12.408822), # India
'New Delhi': ('28.635308', '77.22496', 213.999054), # India
'Philadelphia': ('39.952335', '-75.163789', 12.465688), # United States
'Rio de Janeiro': ('-22.9035393', '-43.2095869', 9.521935), # Brazil
'Tel Aviv': ('32.0599254', '34.7851264', 21.114218), # Israel
'Vienna': ('48.20662', '16.38282', 170.493149), # Austria
'Abu Dhabi': ('24.4666667', '54.3666667', 6.296038), # United Arab Emirates
'Almaty': ('43.255058', '76.912628', 785.522156), # Kazakhstan
'Birmingham': ('52.4829614', '-1.893592', 141.448563), # United Kingdom
'Bogota': ('4.5980556', '-74.0758333', 2614.037109), # Colombia
'Bratislava': ('48.1483765', '17.1073105', 155.813446), # Slovakia
'Brisbane': ('-27.4709331', '153.0235024', 28.163914), # Australia
'Bucharest': ('44.437711', '26.097367', 80.407768), # Romania
'Cairo': ('30.064742', '31.249509', 20.248013), # Egypt
'Cleveland': ('41.4994954', '-81.6954088', 198.879639), # United States
'Cologne': ('50.9406645', '6.9599115', 59.181450), # Germany
'Detroit': ('42.331427', '-83.0457538', 182.763428), # United States
'Dubai': ('25.2644444', '55.3116667', 8.029230), # United Arab Emirates
'Ho Chi Minh City': ('10.75918', '106.662498', 10.757121), # Vietnam
'Kiev': ('50.45', '30.5233333', 157.210175), # Ukraine
'Lima': ('-12.0433333', '-77.0283333', 154.333740), # Peru
'Lisbon': ('38.7070538', '-9.1354884', 2.880179), # Portugal
'Manchester': ('53.4807125', '-2.2343765', 57.892406), # United Kingdom
'Montevideo': ('-34.8833333', '-56.1666667', 45.005032), # Uruguay
'Oslo': ('59.9127263', '10.7460924', 10.502326), # Norway
'Rotterdam': ('51.924216', '4.481776', 2.766272), # The Netherlands
'Riyadh': ('24.6880015', '46.7224333', 613.475281), # Saudi Arabia
'Seattle': ('47.6062095', '-122.3320708', 53.505501), # United States
'Stuttgart': ('48.7771056', '9.1807688', 249.205185), # Germany
'The Hague': ('52.0698576', '4.2911114', 3.686689), # The Netherlands
'Vancouver': ('49.248523', '-123.1088', 70.145927), # Canada
'Adelaide': ('-34.9305556', '138.6205556', 49.098354), # Australia
'Antwerp': ('51.21992', '4.39625', 7.296879), # Belgium
'Arhus': ('56.162939', '10.203921', 26.879421), # Denmark
'Baltimore': ('39.2903848', '-76.6121893', 10.258920), # United States
'Bangalore': ('12.9715987', '77.5945627', 911.858398), # India
'Bologna': ('44.4942191', '11.3464815', 72.875923), # Italy
'Brazilia': ('-14.235004', '-51.92528', 259.063477), # Brazil
'Calgary': ('51.045', '-114.0572222', 1046.000000), # Canada
'Cape Town': ('-33.924788', '18.429916', 5.838447), # South Africa
'Colombo': ('6.927468', '79.848358', 9.969995), # Sri Lanka
'Columbus': ('39.9611755', '-82.9987942', 237.651932), # United States
'Dresden': ('51.0509912', '13.7336335', 114.032356), # Germany
'Edinburgh': ('55.9501755', '-3.1875359', 84.453995), # United Kingdom
'Genoa': ('44.4070624', '8.9339889', 35.418076), # Italy
'Glasgow': ('55.8656274', '-4.2572227', 38.046883), # United Kingdom
'Gothenburg': ('57.6969943', '11.9865', 15.986326), # Sweden
'Guangzhou': ('23.129163', '113.264435', 18.892920), # China
'Hanoi': ('21.0333333', '105.85', 20.009024), # Vietnam
'Kansas City': ('39.1066667', '-94.6763889', 274.249390), # United States
'Leeds': ('53.7996388', '-1.5491221', 47.762367), # United Kingdom
'Lille': ('50.6371834', '3.0630174', 28.139490), # France
'Marseille': ('43.2976116', '5.3810421', 24.785774), # France
'Richmond': ('37.542979', '-77.469092', 63.624462), # United States
'St. Petersburg': ('59.939039', '30.315785', 11.502971), # Russian Federation
'Tashkent': ('41.2666667', '69.2166667', 430.668427), # Uzbekistan
'Tehran': ('35.6961111', '51.4230556', 1180.595947), # Iran
'Tijuana': ('32.533489', '-117.018204', 22.712011), # Mexico
'Turin': ('45.0705621', '7.6866186', 234.000000), # Italy
'Utrecht': ('52.0901422', '5.1096649', 7.720881), # The Netherlands
'Wellington': ('-41.2924945', '174.7732353', 17.000000), # New Zealand
}
def city(name):
try:
data = _city_data[name]
except KeyError:
raise KeyError('Unknown city: %r' % (name,))
o = ephem.Observer()
o.name = name
o.lat, o.lon, o.elevation = data
o.compute_pressure()
return o
def lookup(address):
"""Given a string `address`, do a Google lookup and return an Observer.
Avoid calling this very often, to honor Google's terms of service.
Instead you can run it once, print out the result, and cut and paste
the Observer back into your code to use as often as you like!
"""
parameters = urlencode({'address': address, 'sensor': 'false'})
url = 'http://maps.googleapis.com/maps/api/geocode/json?' + parameters
data = json.loads(urlopen(url).read().decode('utf-8'))
results = data['results']
if not results:
raise ValueError('Google cannot find a place named %r' % address)
address_components = results[0]['address_components']
location = results[0]['geometry']['location']
o = ephem.Observer()
o.name = ', '.join(c['long_name'] for c in address_components)
o.lat = radians(location['lat'])
o.lon = radians(location['lng'])
return o
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