Chapter 13 Examples Updated for the Twitter v2 APIs

Both the v1.1 and v2 examples are posted and the folder names are updated accordingly.

Author: pdeitel

examples/ch13/Thumbs.db examples/ch13_TwitterV1.1/Thumbs.db

@@ -0,0 +1,16 @@
+# Upgrading from Twitter v1.1 to Twitter v2
+
+On August 18, 2022, we discovered that **new** Twitter developer accounts cannot access the Twitter version 1.1 APIs on which we based Chapter 13, Data Mining Twitter, and two case studies in Chapter 17, Big Data: Hadoop, Spark, NoSQL and IoT. 
+
+Twitter users who already had Twitter developer accounts can still access the Twitter version 1.1 APIs, but most students and some instructors will not fall into this category.
+ 
+We’ve already rewritten Chapter 13 to the Twitter version 2 APIs and will be rewriting the two Twitter-based Chapter 17 case studies soon. 
+
+The updated chapter is posted on the book's webpage:
+https://deitel.com/intro-to-python-for-computer-science-and-data-science/
+
+Once completed, we’ll post updated versions of:
+* the Chapter 17 Twitter-based case studies 
+* the instructor materials to the Pearson Instructor Resource Center (IRC), which is accessible only to qualified instructors. 
+ 
+Questions? Please email [email protected].

examples/ch13_TwitterV1.1/_READ_ME_FIRST

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+# Upgrading from Twitter v1.1 to Twitter v2
+
+On August 18, 2022, we discovered that **new** Twitter developer accounts cannot access the Twitter version 1.1 APIs on which we based Chapter 13, Data Mining Twitter, and two case studies in Chapter 17, Big Data: Hadoop, Spark, NoSQL and IoT. 
+
+Twitter users who already had Twitter developer accounts can still access the Twitter version 1.1 APIs, but most students and some instructors will not fall into this category.
+ 
+We’ve already rewritten Chapter 13 to the Twitter version 2 APIs and will be rewriting the two Twitter-based Chapter 17 case studies soon. 
+
+The updated chapter is posted on the book's webpage:
+https://deitel.com/intro-to-python-for-computer-science-and-data-science/
+
+Once completed, we’ll post updated versions of:
+* the Chapter 17 Twitter-based case studies 
+* the instructor materials to the Pearson Instructor Resource Center (IRC), which is accessible only to qualified instructors. 
+ 
+Questions? Please email [email protected].

examples/ch13/keys.py examples/ch13_TwitterV1.1/keys.py

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+bearer_token = 'YourBearerToken'
+mapquest_key = 'YourAPIKey'

examples/ch13/locationlistener.py examples/ch13_TwitterV1.1/locationlistener.py

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+# locationlistener.py
+"""Receives tweets matching a search string and stores a list of
+dictionaries containing each tweet's username/text/location."""
+import tweepy
+from tweetutilities import get_tweet_content
+
+class LocationListener(tweepy.StreamingClient):
+    """Handles incoming Tweet stream to get location data."""
+
+    def __init__(self, bearer_token, counts_dict, 
+                 tweets_list, topic, limit=10):
+        """Configure the LocationListener."""
+        self.tweets_list = tweets_list
+        self.counts_dict = counts_dict
+        self.topic = topic
+        self.TWEET_LIMIT = limit
+        super().__init__(bearer_token, wait_on_rate_limit=True) 
+
+    def on_response(self, response):
+        """Called when Twitter pushes a new tweet to you."""
+
+        # get tweet's username, text and location
+        tweet_data = get_tweet_content(response)  
+        
+        # ignore retweets and tweets that do not contain the topic
+        if (tweet_data['text'].startswith('RT') or
+            self.topic.lower() not in tweet_data['text'].lower()):
+            return
+
+        self.counts_dict['total_tweets'] += 1 # it's an original tweet
+
+        # ignore tweets with no location
+        if not tweet_data.get('location'):  
+            return
+
+        self.counts_dict['locations'] += 1 # user account has location
+        self.tweets_list.append(tweet_data) # store the tweet
+        print(f"{tweet_data['username']}: {tweet_data['text']}\n")
+
+        # if TWEET_LIMIT is reached, terminate streaming
+        if self.counts_dict['locations'] == self.TWEET_LIMIT:
+            self.disconnect()
+
+
+
+##########################################################################
+# (C) Copyright 2022 by Deitel & Associates, Inc. and                    #
+# Pearson Education, Inc. All Rights Reserved.                           #
+#                                                                        #
+# DISCLAIMER: The authors and publisher of this book have used their     #
+# best efforts in preparing the book. These efforts include the          #
+# development, research, and testing of the theories and programs        #
+# to determine their effectiveness. The authors and publisher make       #
+# no warranty of any kind, expressed or implied, with regard to these    #
+# programs or to the documentation contained in these books. The authors #
+# and publisher shall not be liable in any event for incidental or       #
+# consequential damages in connection with, or arising out of, the       #
+# furnishing, performance, or use of these programs.                     #
+##########################################################################

examples/ch13/sentimentlistener.py examples/ch13_TwitterV1.1/sentimentlistener.py

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+# sentimentlisener.py
+"""Searches for tweets that match a search string and tallies 
+the number of positive, neutral and negative tweets."""
+import keys
+import preprocessor as p 
+import sys
+from textblob import TextBlob
+import tweepy
+
+class SentimentListener(tweepy.StreamingClient):
+    """Handles incoming Tweet stream."""
+
+    def __init__(self, bearer_token, sentiment_dict, topic, limit=10):
+        """Configure the SentimentListener."""
+        self.sentiment_dict = sentiment_dict
+        self.tweet_count = 0
+        self.topic = topic
+        self.TWEET_LIMIT = limit
+        
+        # set tweet-preprocessor to remove URLs/reserved words
+        p.set_options(p.OPT.URL, p.OPT.RESERVED) 
+        super().__init__(bearer_token, wait_on_rate_limit=True)
+
+    def on_response(self, response):
+        """Called when Twitter pushes a new tweet to you."""
+
+        # if the tweet is not a retweet
+        if not response.data.text.startswith('RT'):
+            text = p.clean(response.data.text) # clean the tweet
+
+            # ignore tweet if the topic is not in the tweet text
+            if self.topic.lower() not in text.lower():
+                return
+
+            # update self.sentiment_dict with the polarity
+            blob = TextBlob(text)
+            if blob.sentiment.polarity > 0:
+                sentiment = '+'
+                self.sentiment_dict['positive'] += 1 
+            elif blob.sentiment.polarity == 0:
+                sentiment = ' '
+                self.sentiment_dict['neutral'] += 1 
+            else:
+                sentiment = '-'
+                self.sentiment_dict['negative'] += 1 
+
+            # display the tweet
+            username = response.includes['users'][0].username
+            print(f'{sentiment} {username}: {text}\n')
+
+            self.tweet_count += 1 # track number of tweets processed
+
+            # if TWEET_LIMIT is reached, terminate streaming
+            if self.tweet_count == self.TWEET_LIMIT:
+                self.disconnect()
+
+def main():
+    # get search term and number of tweets
+    search_key = sys.argv[1]
+    limit = int(sys.argv[2]) # number of tweets to tally
+    
+    # set up the sentiment dictionary
+    sentiment_dict = {'positive': 0, 'neutral': 0, 'negative': 0}
+
+    # create the StreamingClient subclass object
+    sentiment_listener = SentimentListener(keys.bearer_token, 
+        sentiment_dict, search_key, limit)
+
+    # redirect sys.stderr to sys.stdout
+    sys.stderr = sys.stdout
+
+    # delete existing stream rules
+    rules = sentiment_listener.get_rules().data
+    rule_ids = [rule.id for rule in rules]
+    sentiment_listener.delete_rules(rule_ids)    
+
+    # create stream rule
+    sentiment_listener.add_rules(
+        tweepy.StreamRule(f'{search_key} lang:en'))
+    
+    # start filtering English tweets containing search_key
+    sentiment_listener.filter(expansions=['author_id'])
+
+    print(f'Tweet sentiment for "{search_key}"')
+    print('Positive:', sentiment_dict['positive'])
+    print(' Neutral:', sentiment_dict['neutral'])
+    print('Negative:', sentiment_dict['negative'])
+
+# call main if this file is executed as a script
+if __name__ == '__main__':
+    main()
+
+##########################################################################
+# (C) Copyright 2022 by Deitel & Associates, Inc. and                    #
+# Pearson Education, Inc. All Rights Reserved.                           #
+#                                                                        #
+# DISCLAIMER: The authors and publisher of this book have used their     #
+# best efforts in preparing the book. These efforts include the          #
+# development, research, and testing of the theories and programs        #
+# to determine their effectiveness. The authors and publisher make       #
+# no warranty of any kind, expressed or implied, with regard to these    #
+# programs or to the documentation contained in these books. The authors #
+# and publisher shall not be liable in any event for incidental or       #
+# consequential damages in connection with, or arising out of, the       #
+# furnishing, performance, or use of these programs.                     #
+##########################################################################