├── README.md
├── SocialProfiles-LogicLady.py
└── _config.yml


/README.md:
--------------------------------------------------------------------------------
1 | # **email-saga**
2 | ### Extract Social Media Profiles and Associated Data: <br> Tell a Story Using Just an Email Address!    
3 | + Written in **python 3** using packages `pandas` and `python-intercom`
4 | + Input: `csv` for processing many email addresses at onc
5 | + Output: `csv` for easy review of collected social media data
6 | 


--------------------------------------------------------------------------------
/SocialProfiles-LogicLady.py:
--------------------------------------------------------------------------------
 1 | # pandas and python-intercom packages need to be installed via pip
 2 | import pandas
 3 | from intercom.client import Client
 4 | ### USER INPUT
 5 | INTERCOM_ACCESS_TOKEN = 'dG9rOjQ2MmM2MzlkXzQwNzRfNGVkYl84YjYwXzkwZDVmNzcyMzcyMjoxOjA='
 6 | INPUT_FILE = 'emails.csv'
 7 | OUTPUT_FILE = 'SocialProfiles-out.csv'
 8 | EMAILS_HEADER = 'Emails'
 9 | 
10 | # intercom API extended access token
11 | intercom = Client(personal_access_token=INTERCOM_ACCESS_TOKEN)
12 | # create dataframe from input CSV which should be in the same directory and have column A listing email addresses with header 'Emails'
13 | df = pandas.DataFrame(pandas.read_csv(INPUT_FILE))
14 | 
15 | sites = [
16 | 	['Twitter', 'Twitter Username', [], 'Twitter URL', []],
17 | 	['Facebook', 'Facebook Username', [], 'Facebook URL', []],
18 | 	['LinkedIn', 'LinkedIn Username', [], 'LinkedIn URL', []],
19 | 	['Klout', 'Klout Username', [], 'Klout URL', []],
20 | 	['Vimeo', 'Vimeo Username', [], 'Vimeo URL', []],
21 | 	['GooglePlus', 'Google Plus Username', [], 'Google Plus URL', []],
22 | 	['Flickr', 'Flickr Username', [], 'Flickr URL', []],
23 | 	['Github', 'GitHub Username', [], 'GitHub URL', []],
24 | 	['Foursquare', 'FourSquare Username', [], 'FourSquare URL', []],
25 | 	['YouTube', 'YouTube Username', [], 'YouTube URL', []],
26 | 	['Myspace', 'MySpace Username', [], 'MySpace URL', []],
27 | 	['Tumblr', 'Tumblr Username', [], 'Tumblr URL', []]
28 | ]
29 | others = ['Other Username', [], 'Other URL', [], 'Other Type', []]
30 | avatars = ['Avatar URL', []]
31 | titles = ['Job Title', []]
32 | 
33 | site_list = []
34 | emailnum = 0
35 | 
36 | for site in sites:
37 | 	site_list.append(site[0])
38 | 
39 | for email in df[EMAILS_HEADER]:
40 | 	emailnum += 1
41 | 	intercom.users.create(email=email)
42 | 	user = intercom.users.find(email=email)
43 | 	avatars[1].append(user.avatar.image_url)
44 | 	if len(user.custom_attributes) > 0:
45 | 		if str(user.custom_attributes)[2:11] == 'job_title':
46 | 			titles[1].append(str(user.custom_attributes)[15:len(str(user.custom_attributes))-2])
47 | 		else: 
48 | 			print("Unknown Custom Attribute: " + user.custom_attributes)
49 | 	for profile in user.social_profiles:
50 | 		for site in sites:
51 | 			if profile.name == site[0]: 
52 | 				site[2].append(profile.username)
53 | 				site[4].append(profile.url)
54 | 		if profile.name not in site_list:
55 | 			others[1].append(profile.username)
56 | 			others[3].append(profile.url)
57 | 			others[5].append(profile.name)
58 | 	for l in (others[1], others[3], others[5], titles[1]):
59 | 		if len(l) < emailnum:
60 | 			l.append("")
61 | 	for site in sites:
62 | 		if len(site[2]) < emailnum: 
63 | 			site[2].append("")
64 | 		if len(site[4]) < emailnum: 
65 | 			site[4].append("")
66 | 
67 | # add arrays to dataframe
68 | for site in sites:
69 | 	df[site[1]] = pandas.Series(site[2])
70 | 	df[site[3]] = pandas.Series(site[4])
71 | df[others[0]] = pandas.Series(others[1])
72 | df[others[2]] = pandas.Series(others[3])
73 | df[others[4]] = pandas.Series(others[5])
74 | df[avatars[0]] = pandas.Series(avatars[1])
75 | df[titles[0]] = pandas.Series(titles[1])
76 | # Write dataframe to output CSV
77 | df.to_csv(OUTPUT_FILE,index=False)
78 | 


--------------------------------------------------------------------------------
/_config.yml:
--------------------------------------------------------------------------------
1 | theme: jekyll-theme-time-machine


--------------------------------------------------------------------------------