tweet_graph.py

import re # regular expression
import tweepy 
from tweepy import OAuthHandler #authenication 
from textblob import TextBlob #text/tweet parse

 
class TwitterClient(object):
    '''
    Generic Twitter Class for sentiment analysis.
    '''
    def __init__(self):
        '''
        Class constructor or initialization method.
        '''
        # keys and tokens from the Twitter Dev Console
        consumer_key = 'TL7RyLnfilYH6xaoAlS0XFDCg'
        consumer_secret = 'u5uBn4P62PMIxT4uwUVTl1Ycx4rsfByFs6jl2e4SQ9zDjPIzCO'
        access_token = '919434545924935681-2woCDEXuXQdhJewDaCRBqHBYmi5SFDN'
        access_token_secret = 'T29jqUm6rZqsRYO7AGc47GlgYTaAaN5OtJD0DATo1uBjh'

 
        # attempt authentication
        try:
            # create OAuthHandler object
            self.auth = OAuthHandler(consumer_key, consumer_secret)
            # set access token and secret
            self.auth.set_access_token(access_token, access_token_secret)
            # create tweepy API object to fetch tweets
            self.api = tweepy.API(self.auth)
            print('auth. success')
            
            
        except:
            print("Error: Authentication Failed")
 
    def clean_tweet(self, tweet):
        '''
        Utility function to clean tweet text by removing links, special characters
        using simple regex statements.
        '''
        return ' '.join(re.sub("(@[A-Za-z0-9]+)|([^0-9A-Za-z \t]) |(\w+:\/\/\S+)", " ", tweet).split())
    
 
    def get_tweet_sentiment(self, tweet):
        '''
        Utility function to classify sentiment of passed tweet
        using textblob's sentiment method
        '''
        # create TextBlob object of passed tweet text
        analysis = TextBlob(self.clean_tweet(tweet))
        # set sentiment
        if analysis.sentiment.polarity > 0:
            return 'positive'
        elif analysis.sentiment.polarity == 0:
            return 'neutral'
        else:
            return 'negative'
 
    def get_tweets(self, query, count=200):
        '''
        Main function to fetch tweets and parse them.
        '''
        # empty list to store parsed tweets
        tweets = []
 
        try:
            # call twitter api to fetch tweets
            fetched_tweets = self.api.search(q = query, count = count)
 
            # parsing tweets one by one
            for tweet in fetched_tweets:
                # empty dictionary to store required params of a tweet
                parsed_tweet = {}
 
                # saving text of tweet
                parsed_tweet['text'] = tweet.text
                # saving sentiment of tweet
                parsed_tweet['sentiment'] = self.get_tweet_sentiment(tweet.text)
 
                # appending parsed tweet to tweets list
                if tweet.retweet_count > 0:
                    # if tweet has retweets, ensure that it is appended only once
                    if parsed_tweet not in tweets:
                        tweets.append(parsed_tweet)
                else:
                    tweets.append(parsed_tweet)
 
            # return parsed tweets
            return tweets
 
        except tweepy.TweepError as e:
            # print error (if any)
            print("Error : " + str(e))


def get_tweet_result(leader):    

    #print(leader)
     # creating object of TwitterClient Class
    api = TwitterClient()
    # calling function to get tweets
    tweets = api.get_tweets(query = leader, count = 100)
    #print(tweets)
    
    # picking positive tweets from tweets
    ptweets = [tweet for tweet in tweets if tweet['sentiment'] == 'positive']
    
    result=[];                           
    # percentage of positive tweets
    #print("Positive tweets percentage: {} %".format(100*len(ptweets)/len(tweets)))
    result.append(format(100*len(ptweets)/len(tweets)))
    
    # picking negative tweets from tweets
    ntweets = [tweet for tweet in tweets if tweet['sentiment'] == 'negative']
    # percentage of negative tweets
    #print("Negative tweets percentage: {} %".format(100*len(ntweets)/len(tweets)))
    result.append(format(100*len(ntweets)/len(tweets)))
    # percentage of neutral tweets
    #print("Neutral tweets percentage: {} %".format(100*(len(tweets) - len(ntweets) - len(ptweets))/len(tweets)))
    result.append(format(100*(len(tweets) - len(ntweets) - len(ptweets))/len(tweets)))

    return result