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Python 对LinkedIn用户联系人的地址进行地理编码
CODE:
#!/usr/bin/python # -*- coding: utf-8 -*- ''' Created on 2014-8-20 @author: guaguastd @name: geocode_connection_bing.py ''' from geopy import geocoders import json GEO_APP_KEY = '' g = geocoders.Bing(GEO_APP_KEY) # access to linkedin api from login import linkedin_login linkedin_api = linkedin_login() connections = linkedin_api.get_connections() connections_data = http://www.mamicode.com/r'E:/eclipse/LinkedIn/dfile/linkedin_connections.json'>
RESULT:{u'United States': [Location(United States 39 27m 0.0s N, 98 57m 0.0s W)], u'Chengdu, Sichuan, China': [Location(Chengdu, Sichuan, China 30 40m 0.0s N, 104 5m 0.0s E)], u'Beijing City, China': [Location(Beijing, Beijing, China 39 54m 0.0s N, 116 23m 0.0s E)], u'China': [Location(China 36 33m 0.0s N, 103 59m 0.0s E)], u'San Francisco Bay Area': [Location(CA, United States 37 43m 0.0s N, 122 15m 0.0s W)], u'Foshan, Guangdong, China': [Location(Foshan, Guangdong, China 23 2m 0.0s N, 113 6m 0.0s E)], u'Xingtai, Hebei, China': [Location(Xingtai, Hebei, China 37 4m 0.0s N, 114 29m 0.0s E)], u'Birmingham, United Kingdom': [Location(Birmingham, England, United Kingdom 52 29m 0.0s N, 1 55m 0.0s W), Location(Birmingham, England, United Kingdom 52 27m 0.0s N, 1 43m 0.0s W), Location(Birmingham Airport, England, United Kingdom 52 27m 0.0s N, 1 44m 0.0s W), Location(Birmingham Business Park, England, United Kingdom 52 28m 0.0s N, 1 43m 0.0s W)]}
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