Fixing various long code lines. Hopefully, they're all less than 86 c…

…olumns wide now

recipe__analyze_users_in_search_results.py

@@ -12,7 +12,8 @@ def analyze_users_in_search_results(t, q, max_pages=15, results_per_page=100):
     search_api = twitter.Twitter(domain="search.twitter.com")
     search_results = []
     for page in range(1,max_pages+1):
-        search_results += search_api.search(q=q, rpp=results_per_page, page=page)['results']
+        search_results += \
+            search_api.search(q=q, rpp=results_per_page, page=page)['results']
 
     # Extract the screen names (the "from_user" field) from the results
     # and optionally map them to a useful field like the tweet id
@@ -30,18 +31,21 @@ def analyze_users_in_search_results(t, q, max_pages=15, results_per_page=100):
         screen_name_to_tweet_ids[screen_name] += [ result['id'] ]
 
 
-    # Use the /users/lookup resource to resolve profile information for these screen names
+    # Use the /users/lookup resource to resolve profile information for 
+    # these screen names
 
     screen_name_to_info = get_info_by_screen_name(t, screen_name_to_tweet_ids.keys())
 
-    # Extract the home location for each user. Note that the "location" field can be anything
-    # a user has typed in, and may be something like "Everywhere", "United States" or something else
-    # that won't geocode to a specific coordinate on a map.
+    # Extract the home location for each user. Note that the "location" field can 
+    # be anything a user has typed in, and may be something like "Everywhere", 
+    # "United States" or something else that won't geocode to a specific coordinate 
+    # on a map.
 
-    screen_name_to_location = dict([(sn, info['location']) for sn, info in screen_name_to_info.items()])
+    screen_name_to_location = dict([(sn, info['location']) 
+                                    for sn, info in screen_name_to_info.items()])
 
-    # Use the various screen_name_to{tweet_ids, info, location} maps to determine interesting things about 
-    # the people who appear in the search results.
+    # Use the various screen_name_to{tweet_ids, info, location} maps to determine 
+    # interesting things about the people who appear in the search results.
 
     return screen_name_to_info, screen_name_to_location, screen_name_to_tweet_ids
 

recipe__crawl.py

@@ -17,7 +17,8 @@ def get_all_followers_ids(user_id, limit):
         ids = []
         while cursor != 0:
 
-            response = make_twitter_request(t, t.followers.ids, user_id=user_id, cursor=cursor)
+            response = make_twitter_request(t, t.followers.ids,
+                                            user_id=user_id, cursor=cursor)
 
             if response is not None:
                 ids += response['ids']
@@ -50,8 +51,8 @@ def get_all_followers_ids(user_id, limit):
             for _fid in queue:
                 _follower_ids = get_all_followers_ids(user_id=_fid, limit=limit)
 
-                # Store a fid => _follower_ids mapping in Redis or other database of choice
-                # In Redis, it might look something like this:
+                # Store a fid => _follower_ids mapping in Redis or other 
+                # database of choice. In Redis, it might look something like this:
 
                 rid = get_redis_id('follower_ids', user_id=fid)
                 [ r.sadd(rid, _id) for _id in _follower_ids ] 

recipe__dorling_cartogram.py

@@ -126,8 +126,11 @@ def get_state_frequencies(locations):
 shutil.copytree('etc/protovis/protovis-3.2',
                 'out/protovis-3.2')
 
-html = open('etc/protovis/dorling_cartogram/dorling_cartogram.html').read() % (json.dumps(json_data),)
-f = open(os.path.join(os.getcwd(), 'out', 'dorling_cartogram', 'dorling_cartogram.html'), 'w')
+html = open('etc/protovis/dorling_cartogram/dorling_cartogram.html').read() % \
+        (json.dumps(json_data),)
+
+f = open(os.path.join(os.getcwd(), 'out', 'dorling_cartogram', 
+                      'dorling_cartogram.html'), 'w')
 f.write(html)
 f.close()
 

recipe__geocode_profile_locations.py

@@ -8,9 +8,9 @@
 
 def geocode_locations(geocoder, locations):
 
-    # Some basic replacement transforms may be necessary for geocoding services to function properly
-    # You may probably need to add your own as you encounter rough edges in the data or with the geocoding
-    # service you settle on. For example, ...
+    # Some basic replacement transforms may be necessary for geocoding services to 
+    # function properly. You may probably need to add your own as you encounter rough
+    # edges in the data or with the geocoding service you settle on. For example, ...
 
     replacement_transforms = [('San Francisco Bay', 'San Francisco')]
 
@@ -24,11 +24,11 @@ def geocode_locations(geocoder, locations):
         if location_to_coords.has_key(location):
             continue
 
-        transformed_location = location
+        xformed_location = location
 
         for transform in replacement_transforms:
 
-            transformed_location = transformed_location.replace(*transform)
+            xformed_location = xformed_location.replace(*transform)
 
             while True:
 
@@ -37,39 +37,41 @@ def geocode_locations(geocoder, locations):
                 try:
                     # This call returns a generator
 
-                    results = geocoder.geocode(transformed_location, exactly_one=False)
+                    results = geocoder.geocode(xformed_location, exactly_one=False)
                     break
                 except HTTPError, e:
                     num_errors += 1
                     if num_errors >= MAX_HTTP_ERRORS:
                         sys.exit()
                     print >> sys.stderr, e.message
-                    print >> sys.stderr, 'Encountered an urllib2 error. Trying again...'
+                    print >> sys.stderr, 'A urllib2 error. Retrying...'
                 except UnicodeEncodeError, e:
                     print >> sys.stderr, e
-                    print >> sys.stderr, 'Encountered a UnicodeEncodeError...', e.message
+                    print >> sys.stderr, 'A UnicodeEncodeError...', e.message
                     break
                 except geopy.geocoders.google.GQueryError, e:
                     print >> sys.stderr, e
-                    print >> sys.stderr, 'Encountered a ...GQueryError', e.message
+                    print >> sys.stderr, 'A GQueryError', e.message
                     break
 
 
         for result in results:
 
             # Each result is of the form ("Description", (X,Y))
-            # Unless you have a some special logic for picking the best of many possible
-            # results, choose the first one returned in results and move along
+            # Unless you have a some special logic for picking the best of many 
+            # possible results, choose the first one returned in results and move 
+            # along
 
             location_to_coords[location] = result[1]
             location_to_description[location] = result[0]
             break
 
-    # Use location_to_coords and other information of interest to populate a visualization.
-    # Depending on your particular needs, it is highly likely that you'll want to further
-    # post process the geocoded locations to filter out locations such as "U.S.A." which will
-    # plot a placemarker in the geographic center of the United States yet make the visualization
-    # look skewed in favor of Oklahoma, for example.
+    # Use location_to_coords and other information of interest to populate a 
+    # visualization. Depending on your particular needs, it is highly likely that 
+    # you'll want to further post process the geocoded locations to filter out 
+    # location such as "U.S.A." which will plot a placemarker in the geographic 
+    # center of the United States yet make the visualization look skewed in favor
+    # of places like Oklahoma, for example.
 
     return location_to_coords, location_to_description
 
@@ -91,8 +93,8 @@ def geocode_locations(geocoder, locations):
 
     t = oauth_login()
 
-    # This function returns a few useful maps. Let's use the screen_name => location map and
-    # geocode the locations
+    # This function returns a few useful maps. Let's use the 
+    # screen_name => location map and geocode the locations
 
     _, screen_name_to_location, _ = analyze_users_in_search_results(t, Q, 2)
 

recipe__get_rt_origins.py

@@ -17,10 +17,14 @@ def get_rt_origins(tweet):
         if tweet['retweet_count'] > 0:
             rt_origins += [ tweet['user']['name'].lower() ]
 
-    # Also, inspect the tweet for the presence of "legacy" retweet patterns such as "RT" and "via"
+    # Also, inspect the tweet for the presence of "legacy" retweet 
+    # patterns such as "RT" and "via"
 
     try:
-        rt_origins += [ mention.strip() for mention in rt_patterns.findall(tweet['text'])[0][1].split() ]
+        rt_origins += [ 
+                        mention.strip() 
+                        for mention in rt_patterns.findall(tweet['text'])[0][1].split() 
+                      ]
     except IndexError, e:
         pass
 
@@ -34,30 +38,30 @@ def get_rt_origins(tweet):
     # Assume tweets have been fetched from the /search resource or elsewhere.
 
     tweets = \
-        [
-           {
-            'text' : 'RT @ptowbrussell Get @SocialWebMining example code at http://bit.ly/biais2 #w00t'
+    [
+       {
+        'text' : 'RT @ptowbrussell Get @SocialWebMining at http://bit.ly/biais2 #w00t'
 
-            # ... more tweet fields ...
+        # ... more tweet fields ...
 
-           },
+       },
 
-           {
-            'text' : 'Get @SocialWebMining example code at http://bit.ly/biais2 #w00t',
-            'retweet_count' : 1,
-            'user' : { 
-             'name' : 'ptwobrussell'
+       {
+        'text' : 'Get @SocialWebMining example code at http://bit.ly/biais2 #w00t',
+        'retweet_count' : 1,
+        'user' : { 
+         'name' : 'ptwobrussell'
 
-                # ... more user fields ...
-            }
+            # ... more user fields ...
+        }
 
-            # ... more tweet fields ...
+        # ... more tweet fields ...
 
-           },
-
-           # ... more tweets ...
+       },
 
-        ]
+       # ... more tweets ...
+
+    ]
 
     for tweet in tweets:
         print get_rt_origins(tweet) 

recipe__get_search_results_for_trending_topic.py

@@ -37,7 +37,8 @@
 
 search_results = []
 for page in range(1,MAX_PAGES+1):
-    search_results += twitter_search.search(q=q, rpp=RESULTS_PER_PAGE, page=page)['results']
+    search_results += \
+        twitter_search.search(q=q, rpp=RESULTS_PER_PAGE, page=page)['results']
 
 # Exract tweet entities and embed them into search results
 

recipe__harvest_timeline.py

@@ -102,10 +102,10 @@ def max_finding_reducer(keys, values, rereduce):
         KW['since_id'] = 1
 
 # Harvest tweets for the given timeline.
-# For friend and home timelines, the unofficial limitation is about 800 statuses although
-# other documentation may state otherwise. The public timeline only returns 20 statuses 
-# and gets updated every 60 seconds, so consider using the streaming API for public statuses.
-# See http://groups.google.com/group/twitter-development-talk/browse_thread/thread/4678df70c301be43
+# For friend and home timelines, the unofficial limitation is about 800 statuses 
+# although other documentation may state otherwise. The public timeline only returns
+# 20 statuses and gets updated every 60 seconds, so consider using the streaming API 
+# for public statuses. See http://bit.ly/fgJrAx
 # Note that the count and since_id params have no effect for the public timeline
 
 page_num = 1
@@ -114,7 +114,8 @@ def max_finding_reducer(keys, values, rereduce):
     api_call = getattr(t.statuses, TIMELINE_NAME + '_timeline')
     tweets = make_twitter_request(t, api_call, **KW)
 
-    # Actually storing tweets in CouchDB is as simple as passing them into a call to db.update
+    # Actually storing tweets in CouchDB is as simple as passing them 
+    # into a call to db.update
 
     db.update(tweets, all_or_nothing=True)
 

recipe__setwise_operations.py

@@ -55,7 +55,8 @@ def get_redis_id(key_name, screen_name=None, user_id=None):
 
         cursor = response['next_cursor']
 
-        print >> sys.stderr, 'Fetched %i total friend ids for %s' % (r.scard(rid), SCREEN_NAME)
+        print >> sys.stderr, \
+            'Fetched %i total friend ids for %s' % (r.scard(rid), SCREEN_NAME)
 
         if r.scard(rid) >= MAX_IDS:
             break
@@ -80,7 +81,8 @@ def get_redis_id(key_name, screen_name=None, user_id=None):
 
         cursor = response['next_cursor']
 
-        print >> sys.stderr, 'Fetched %i total follower ids for %s' % (r.scard(rid), SCREEN_NAME)
+        print >> sys.stderr, \
+            'Fetched %i total follower ids for %s' % (r.scard(rid), SCREEN_NAME)
 
         if r.scard(rid) >= MAX_IDS:
             break

recipe__tweet_entities_tagcloud.py

@@ -120,12 +120,12 @@ def weightTermByFreq(f):
 if not os.path.isdir('out'):
     os.mkdir('out')
 
-f = open(os.path.join('out', os.path.basename(HTML_TEMPLATE)), 'w')
+f = open(os.path.join(os.getcwd(), 'out', os.path.basename(HTML_TEMPLATE)), 'w')
 f.write(html_page)
 f.close()
 
 print >> sys.stderr, 'Tagcloud stored in: %s' % f.name
 
 # Open up the web page in your browser
 
-webbrowser.open("file://" + os.path.join(os.getcwd(), 'out', os.path.basename(HTML_TEMPLATE)))
+webbrowser.open("file://" + f.name)

recipe__visualize_rt_graph_protovis.py

@@ -29,7 +29,8 @@ def write_protovis_output(g, out_file, html_template):
         links.append({'source' : indexed_nodes[n2], 
                       'target' : indexed_nodes[n1]})
 
-    json_data = json.dumps({"nodes" : [{"nodeName" : n} for n in nodes], "links" : links}, indent=4)
+    json_data = json.dumps({"nodes" : [{"nodeName" : n} for n in nodes], \
+                            "links" : links}, indent=4)
 
     html = open(html_template).read() % (json_data,)
 
@@ -63,7 +64,9 @@ def write_protovis_output(g, out_file, html_template):
     search_results = []
     for page in range(1,MAX_PAGES+1):
 
-        search_results.append(twitter_search.search(q=Q, rpp=RESULTS_PER_PAGE, page=page))
+        search_results.append(twitter_search.search(q=Q, 
+                                                    rpp=RESULTS_PER_PAGE, 
+                                                    page=page))
 
     all_tweets = [  tweet 
                     for page in search_results