made a collection of twitter api solutions

[twitter-api-cdsw-solutions] / solution-geo-1.py

diff --git a/twitter-stream2.py b/solution-geo-1.py
similarity index 56%
rename from twitter-stream2.py
rename to solution-geo-1.py
index 47855d8b657ba3ec813169f628337d95aa01d5b3..3ba56d3b278f938aee35cc6446148d353d043b18 100644 (file)
--- a/twitter-stream2.py
+++ b/solution-geo-1.py
@@ -1,3 +1,10 @@
+# Alter the streaming code to include a "locations" filter. You need
+# to use the order sw_lng, sw_lat, ne_lng, ne_lat for the four
+# coordinates.
+
+# Note: to answer this, I used this website to find a good box:
+# http://boundingbox.klokantech.com/
+

 import encoding_fix
 import tweepy
 from twitter_authentication import CONSUMER_KEY, CONSUMER_SECRET, ACCESS_TOKEN, ACCESS_TOKEN_SECRET
 import encoding_fix
 import tweepy
 from twitter_authentication import CONSUMER_KEY, CONSUMER_SECRET, ACCESS_TOKEN, ACCESS_TOKEN_SECRET


@@ -12,11 +19,12 @@ class StreamListener(tweepy.StreamListener):
         print(tweet.author.screen_name + "\t" + tweet.text)
 
     def on_error(self, status_code):
         print(tweet.author.screen_name + "\t" + tweet.text)
 
     def on_error(self, status_code):

-        print( 'Error: ' + repr(status_code))
+        print('Error: ' + repr(status_code))

         return False
 
 l = StreamListener()
 streamer = tweepy.Stream(auth=auth, listener=l)
 
         return False
 
 l = StreamListener()
 streamer = tweepy.Stream(auth=auth, listener=l)
 

-keywords = ['python', 'perl']
-streamer.filter(track = keywords)
+# This should grab tweets within Seattle:
+streamer.filter(locations=[-122.459696, 47.481002, -122.224433, 47.734136])
+