SocialProfiles-LogicLady.py

# pandas and python-intercom packages need to be installed via pip
import pandas
from intercom.client import Client
### USER INPUT
INTERCOM_ACCESS_TOKEN = 'dG9rOjQ2MmM2MzlkXzQwNzRfNGVkYl84YjYwXzkwZDVmNzcyMzcyMjoxOjA='
INPUT_FILE = 'emails.csv'
OUTPUT_FILE = 'SocialProfiles-out.csv'
EMAILS_HEADER = 'Emails'

# intercom API extended access token
intercom = Client(personal_access_token=INTERCOM_ACCESS_TOKEN)
# create dataframe from input CSV which should be in the same directory and have column A listing email addresses with header 'Emails'
df = pandas.DataFrame(pandas.read_csv(INPUT_FILE))

sites = [
	['Twitter', 'Twitter Username', [], 'Twitter URL', []],
	['Facebook', 'Facebook Username', [], 'Facebook URL', []],
	['LinkedIn', 'LinkedIn Username', [], 'LinkedIn URL', []],
	['Klout', 'Klout Username', [], 'Klout URL', []],
	['Vimeo', 'Vimeo Username', [], 'Vimeo URL', []],
	['GooglePlus', 'Google Plus Username', [], 'Google Plus URL', []],
	['Flickr', 'Flickr Username', [], 'Flickr URL', []],
	['Github', 'GitHub Username', [], 'GitHub URL', []],
	['Foursquare', 'FourSquare Username', [], 'FourSquare URL', []],
	['YouTube', 'YouTube Username', [], 'YouTube URL', []],
	['Myspace', 'MySpace Username', [], 'MySpace URL', []],
	['Tumblr', 'Tumblr Username', [], 'Tumblr URL', []]
]
others = ['Other Username', [], 'Other URL', [], 'Other Type', []]
avatars = ['Avatar URL', []]
titles = ['Job Title', []]

site_list = []
emailnum = 0

for site in sites:
	site_list.append(site[0])

for email in df[EMAILS_HEADER]:
	emailnum += 1
	intercom.users.create(email=email)
	user = intercom.users.find(email=email)
	avatars[1].append(user.avatar.image_url)
	if len(user.custom_attributes) > 0:
		if str(user.custom_attributes)[2:11] == 'job_title':
			titles[1].append(str(user.custom_attributes)[15:len(str(user.custom_attributes))-2])
		else: 
			print("Unknown Custom Attribute: " + user.custom_attributes)
	for profile in user.social_profiles:
		for site in sites:
			if profile.name == site[0]: 
				site[2].append(profile.username)
				site[4].append(profile.url)
		if profile.name not in site_list:
			others[1].append(profile.username)
			others[3].append(profile.url)
			others[5].append(profile.name)
	for l in (others[1], others[3], others[5], titles[1]):
		if len(l) < emailnum:
			l.append("")
	for site in sites:
		if len(site[2]) < emailnum: 
			site[2].append("")
		if len(site[4]) < emailnum: 
			site[4].append("")

# add arrays to dataframe
for site in sites:
	df[site[1]] = pandas.Series(site[2])
	df[site[3]] = pandas.Series(site[4])
df[others[0]] = pandas.Series(others[1])
df[others[2]] = pandas.Series(others[3])
df[others[4]] = pandas.Series(others[5])
df[avatars[0]] = pandas.Series(avatars[1])
df[titles[0]] = pandas.Series(titles[1])
# Write dataframe to output CSV
df.to_csv(OUTPUT_FILE,index=False)