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"""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):
"""DEPRECATED: Google, alas, no longer supports anonymous lat/lon lookup.
Because looking up an address is really a problem in geography, not
astronomy, PyEphem is not planning on repairing this routine. Look
for a good Python geolocation library if you need to turn strings
into latitudes and longitudes.
"""
raise NotImplementedError(lookup.__doc__.split(None, 1)[1].strip())
def lookup_with_geonames(q, username):
"""Given a string `q`, do a geonames lookup and return an Observer.
Free geonames queries require registration with an email address
at this url: https://www.geonames.org/login
After registration, you also must enable the free webservices
through your user account
"""
parameters = urlencode({'q': q, 'username': username})
url = 'http://api.geonames.org/searchJSON?' + parameters
data = json.loads(urlopen(url).read().decode('utf-8'))
if data['totalResultsCount'] == 0:
raise ValueError('geonames cannot find a place named %r' % name)
location = data['geonames'][0]
parameters_elev = urlencode({'lat':location['lat'],
'lng':location['lng'],
'username':username})
url_elev = 'http://api.geonames.org/srtm1JSON?' + parameters_elev
data_elev = json.loads(urlopen(url_elev).read().decode('utf-8'))
o = ephem.Observer()
o.name = location['toponymName']
o.lat = location['lat']
o.lon = location['lng']
o.elevation = data_elev['srtm1']
o.compute_pressure()
return o
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