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Facebook News Feed Word Cloud
#!/usr/bin/env python
import sys
import urllib2
import json
from collections import defaultdict
from nltk import word_tokenize
IGNORED_WORDS = ["!", ".", ",", "(", ")", "'s", ":", "?", "...", "$",
"<", ">", "''", "``", "-", "c", "'", "--", "&",
"and", "the", "or", "not", "i", "you", "to", "this",
"of", "in", "for", "a", "an", "and", "your", "with",
"me", "my", "be", "these", "that", "do", "at", "no", "so",
"1", "2", "3", "4", "5", "6", "7", "8", "9", "0",
"http", "@", "is", "am", "are", "it", "if", "n't", "'em",
"from", "one", "on", "up", "like", "we", "their", "they",
"'ll", "'d", "'m", "//www.youtube.com/watch", "by", "have",
"just", "will", "as"]
def get_json(url):
""" Return the parsed JSON from a url. """
print "GET %s" % url
f = urllib2.urlopen(url)
return json.loads(f.read())
def fb_feed_url(access_token):
""" The graph api url for your facebook feed. access_token should be
a valid facebook access token as a string.
"""
return "https://graph.facebook.com/me/home?access_token=%s" % access_token
def fb_news_feed(access_token):
""" Returns a set number of pages from a facebook news feed as a
list of parsed json.
"""
feed_url = fb_feed_url(access_token)
page_json = []
for x in range(0, 100):
json = get_json(feed_url)
page_json.append(json)
# Break if there's not enough data to continue
if 'paging' in json and 'next' in json['paging']:
feed_url = json['paging']['next']
else:
break
return page_json
def word_count(words):
""" Count the occurrences of each word. Words should be a list of strings
that you might get from str.split() or nltk.word_tokenize().
"""
seen = defaultdict(lambda: 0)
for w in words:
if w.lower() not in IGNORED_WORDS:
seen[w] += 1
return seen
def word_cloud_sizes(counts):
max_count = max(counts.values())
min_size, max_size = (1, 5)
word_sizes = defaultdict(lambda : 1)
for word in counts:
if counts[word] > 1:
size = int(float(counts[word]) * (max_size - 1) / max_count) + 1
word_sizes[word] = size
return word_sizes
def word_cloud_header():
return """
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
<html>
<head>
<title>My Facebook Word Cloud</title>
<style type=\"text/css\">
.size-1 { font-size: 10pt; }
.size-2 { font-size: 16pt; }
.size-3 { font-size: 28pt; }
.size-4 { font-size: 36pt; font-weight: bold; }
.size-5 { font-size: 48pt; font-weight: bold; }
.word-cloud { margin: 0 auto; width: 600px; padding-top: 10px; }
</style>
</head>
<body>
<div class="word-cloud">
"""
def word_cloud_footer():
return """
</div>
</body>
</html>
"""
def word_cloud_html(sizes):
def word_html(word, size):
return "<span class=\"size-%s\">%s</span>" % (size, word)
return ' '.join([word_html(w, s) for w, s in sizes.items()])
if __name__ == "__main__":
access_token = sys.argv[1]
pages = fb_news_feed(access_token)
messages = [post['message'] for page in pages
for post in page['data']
if 'message' in post]
comments = [comment['message'] for page in pages
for post in page['data']
if 'comments' in post and 'data' in post['comments']
for comment in post['comments']['data']
if 'if message' in comment]
messages.extend(comments)
tokens = [token for msg in messages for token in word_tokenize(msg)]
counts = word_count(tokens)
sizes = word_cloud_sizes(counts)
print ''.join([
word_cloud_header(),
word_cloud_html(sizes),
word_cloud_footer()])
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