The document describes a program that automatically monitors USGS earthquake feeds, identifies local quakes near San Francisco, generates short URLs for the quake details, tweets summary information, and records tweeted quakes to avoid duplicates. It fetches XML earthquake data from USGS, parses it to find local quakes, generates and checks for duplicate bitly links, records link and tweets title, link and summary if not a duplicate quake.

1. @sfusgsGeo-tweet my quake…@ayman • yahoo! researchhttp://en.wikipedia.org/wiki/File:San_francisco_1906_earthquake.jpg

2. Zync • Y! Messenger

3. FireEagle

4. FireEagle@ayman

5. http://bit.ly/statler

6. shake and rumble in 2GA

7. http://earthquake.usgs.gov/earthquakes/recenteqsus/Quakes/nc71336726.php

8. Click through maps…

9. A Want Ad

10. USGS lists every quake

11. http://earthquake.usgs.gov/earthquakes/catalogs/

12. http://earthquake.usgs.gov/earthquakes/catalogs/

13. Trust me, it is just XML

14. Yahoo! Search goes to YDN

15. Google Search goes to YDN

16. Bing goes to YDN

17. Using ElementTree

18. The flow was simpleCRON this::cUrl XML feed from USGSfind local quakesbit.ly the quake permalinkif not duplicaterecord this quaketweet this quake

19. def fetch_quakes():def fetch_quakes():api = bitly.Api(login=’ABCDEF', apikey=’12345678901234567890')rss = parse(urllib.urlopen(USGS_URL)).getroot() quakes = [] for element in rss.findall('{%s}entry' % USGS_NS): title = element.findtext('{%s}title' % USGS_NS) if (title.find("San Francisco Bay") > -1): point = element.findtext('{%s}point' % GEORSS_NS) points = point.split(None, 1) link = element.find('{%s}link' % USGS_NS)href = 'http://earthquakes.usgs.gov%s' % link.get('href')href = api.shorten(href) if (is_duplicate(href) is False):f = open(‘urls.txt', 'a')f.write('%s\n' % href)f.close() summary = element.findtext('{%s}summary' % USGS_NS) summary = summary.split("<br>")[1] summary = summary.replace(' at epicenter</p><p>', ' ') summary = strip_tags(summary)quakes.append({'title': element.findtext('{%s}title' % USGS_NS), 'link' : href, 'updated' : element.findtext('{%s}updated' % USGS_NS), 'long' : points[1], 'lat' : points[0], 'elev' : element.findtext('{%s}elev' % GEORSS_NS), 'summary' : summary}) return quakes

20. def is_duplicate(url):def is_duplicate(url): from subprocess import callif(os.path.exists(‘urls.txt') is False): call(['/usr/bin/touch', ‘urls.txt'])r = call(['/bin/fgrep',url, ‘urls.txt']) if (r == 0): return True else: return False

21. def send_tweet(t):def send_tweet(t): import httplib2 username = ’ABCDEFG' password = ’12345678901234567890'msg = ('%s %s %s' % (t['title'], t['link'], t['summary'])) http = httplib2.Http()http.add_credentials(username, password) response = http.request( "http://twitter.com/statuses/update.xml", "POST",urllib.urlencode({"status": msg, "lat": t['lat'], "long": t['long']}) )SEE: http://code.google.com/p/httplib2/ps: you shouldn’t store your passwords like that…this is just an illustration

22. fin

23. Crunched

24. USGS on Open Gov’t

25. Open Questions?How can other local sources be disseminated?How can mass media be filtered so it can be consumed in a similar manner?Can we collect information around the news? For example, find all the tweets that relate to a particular quake.Thanks, @ayman.