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Python script to query your LinkedIn network and get all your network's connections and their interconnections.
#!/usr/bin/env python
# encoding: utf-8
Created by Thomas Cabrol on 2012-12-03.
Customised by Rik Van Bruggen
Copyright (c) 2012 dataiku. All rights reserved.
Building the LinkedIn Graph
import oauth2 as oauth
import urlparse
import simplejson
import codecs
CONSUMER_KEY = "your-consumer-key-here"
CONSUMER_SECRET = "your-consumer-secret-here"
OAUTH_TOKEN = "your-oauth-token-here"
OAUTH_TOKEN_SECRET = "your-oauth-token-secret-here"
OUTPUT = "linked.csv"
def linkedin_connections():
# Use your credentials to build the oauth client
consumer = oauth.Consumer(key=CONSUMER_KEY, secret=CONSUMER_SECRET)
token = oauth.Token(key=OAUTH_TOKEN, secret=OAUTH_TOKEN_SECRET)
client = oauth.Client(consumer, token)
# Fetch first degree connections
resp, content = client.request('')
results = simplejson.loads(content)
# File that will store the results
output =, 'w', 'utf-8')
# Loop thru the 1st degree connection and see how they connect to each other
for result in results["values"]:
con = "%s %s" % (result["firstName"].replace(",", " "), result["lastName"].replace(",", " "))
# Note that you will have to replace "YOURNAME" with YOUR OWN NAME, associated with the username that you are using for the query
print >>output, "%s,%s" % ("YOURNAME", con)
# This is the trick, use the search API to get related connections
u = "" % result["id"]
resp, content = client.request(u)
rels = simplejson.loads(content)
for rel in rels['relationToViewer']['relatedConnections']['values']:
sec = "%s %s" % (rel["firstName"].replace(",", " "), rel["lastName"].replace(",", " "))
print >>output, "%s,%s" % (con, sec)
if __name__ == '__main__':
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