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import feedparser
import re
def get_word_counts(url):
Fetches and parses and RSS feed using a url.
Returns a tuple with a feed's title and
a dictionary of word counts.
parsed = feedparser.parse(url)
word_count = {}
if 'title' in parsed.feed:
for entry in parsed.entries:
if 'summary' in entry:
summary = entry.summary
summary = entry.description
words = get_words(' '.join([entry.title, summary]))
for word in words:
word_count.setdefault(word, 0)
word_count[word] += 1
return (parsed.feed.title, word_count)
return (None, None)
def get_words(html):
Uses regular expressions to remove html tags and to split
the resulting text into single words.
Returns a list of lower cased words.
txt = re.compile(r'<[^>]+').sub('', html)
words = re.compile(r'[^A-Z^a-z]+').split(txt)
return [word.lower() for word in words if word != '']
if __name__ == '__main__':
# turn into callable function for use in interactive python session
# break down into smaller functions for easier understanding
ap_count = {}
word_counts = {}
# iterate through list of feed urls and collect word count for each feed
# then iterate throught that collection and assign the blog count for each word
with open('feedlist.txt', 'rb') as f:
feed_lines = f.readlines()
feed_list_length = len(feed_lines)
c = 0.0
for feed_url in feed_lines:
c += 1
print "%.2f%%" % ((c / feed_list_length) * 100)
title, word_count = get_word_counts(feed_url)
if title:
word_counts[title] = word_count
for word, count in word_count.items():
ap_count.setdefault(word, 0)
if count > 1:
ap_count[word] += 1
word_list = []
# iterate through list of word:blog_count and find the fraction of
# how many times the word appears per all the blogs and if it's
# between 0.1 and 0.5 then append it to word_list
for word, blog_count in ap_count.items():
frac = float(blog_count) / feed_list_length
if frac > 0.1 and frac < 0.5:
# first iterate through the word list and print out the tab separated
# list of words. Then iterate through the word_list again and if the word
# is in word_count, output it's count preceeded by a tab
with open('blogdata2.txt', 'wb') as output:
for word in word_list:
output.write('\t%s' % word.encode('utf8'))
for blog, word_count in word_counts.items():
for word in word_list:
if word in word_count:
output.write('\t%d' % word_count[word])