Sentiment Analysis App mk1.py

import tweepy
from tweepy import Stream
from tweepy import OAuthHandler
from tweepy.streaming import StreamListener
import time
import csv
import collection
import copy



consumer_key = 'KG2opAGBUTm7WOh4kxRH4hkv0'
consumer_secret = 'yMnAZmUJNgPMG52aJppODuCmumiLJAKaofRdOnTc3fmD2BQxmV'
access_token = '2797292249-DpQSv3x81hHuPQCSgyyowyWiQk5nWFQUHz94quG'
access_secret = '0kK2PLwxdiXG7PAyZgBGptvqUO9Aiz5hPsQZHVecqdh8Q'


class listener(StreamListener): # collects the tweets

    def on_data(self, data): #
        tweet = data.split(',"text":"')[1].split('","source')[0]#each tweet is split into 
        tweetData = str(time.time())
        saveFile = open('TwitterDB.csv','a')
        saveFile.write(tweetData+','+tweet)
        saveFile.write('\n')
        saveFile.close()
        time.sleep(100)

    def on_error(self, status):
        print (status)


def tokenizer():
    lTweets = []
    with open('TwitterDB.csv', 'r') as f:
        reader = csv.reader(f)
        for row in reader:
            lTweets.append(row[1])

    for x in range (0, len(lTweets)):
        lTweet = []
        sTweet = lTweets[x]
        lTweet = sTweet.splitline()
        for y in range (0,len(lTweet)):
            sWord = lTweet(y)
            if sWord(len(sWord)-1:len(sWord)) == ",":
                lTweet.insert(y+1,sWord[0:len(sWord)-1])
                lTweet.remove(sTweet)
                lTweet.insert(y+1, ",")
            elif sWord(len(sWord)-1:len(sWord)) == ".":
                lTweet.insert(y+1,sWord[0:len(sWord)-1])
                lTweet.remove(sTweet)
                lTweet.insert(y+1, ".")
            elif sWord(len(sWord)-1:len(sWord)) == "?":
                lTweet.insert(y+1,sWord[0:len(sWord)-1])
                lTweet.remove(sTweet)
                lTweet.insert(y+1, "?")
            elif sWord(len(sWord)-1:len(sWord)) == "!":
                lTweet.insert(y+1,sWord[0:len(sWord)-1])
                lTweet.remove(sTweet)
                lTweet.insert(y+1, "!")



     if sSentence[len(sSentence):len(sSentence)+1] != ".":
        sSentence = sSentence +"."

    lSen = []
    nStor1 = 0
    nStor2 = 0
    nLetter = ""
    sWord = ""
    sNegate = "n't"
    if sSentence[len(sSentence)-1:len(sSentence)]!= ".":
        sSentence = sSentence +"."
    for i in range (0,  len(sSentence)):
        nLetter = ord(sSentence[i:i+1])
        nStor2 = i
        if nLetter == 32:
            sWord = sSentence[nStor1:nStor2]
            if sWord[len(sWord)-3:len(sWord)] == "n't":
                sWord = sWord[0:len(sWord)-3]
                lSen.append(sWord)
                lSen.append(sNegate)
            else:
                lSen.append(sSentence[nStor1:nStor2])
            nStor1 = nStor2+1
        else:
            if nLetter == 44 or nLetter == 46:
                lSen.append(sSentence[nStor1:nStor2])
                nStor1 = nStor2+1
    lSen= [item.lower() for item in lSen]
    sEmpty = ""

    print(lSen)
    return lSen

class AnalyzeTweets(object):

    def __init__(self, tArray):
        self.tArray = tArray

    def sentiment(self):
        lSen = self.tArray
        num_pos_tweets = 0
        num_neg_tweets = 0
        pos_position_list = []
        neg_position_list = []
        nSen = len(lSen)

        positive_words = []
        with open('positive-words.txt') as inputfile:
            for line in inputfile:
                positive_words.append(line.strip())

        negative_words = []
        with open('negative-words.txt') as inputfile:
            for line in inputfile:
                positive_words.append(line.strip())

        for x in range (0, nSen):
            for i in range(0, len(positive_words)):
                if lSen[x] == positive_words[i]:
                    num_pos_tweets = num_pos_tweets + 1
                    pos_position_list.append(x)

        for z in range (0, nSen):
            for y in range(0, len(negative_words)):
                if lSen[z] == negative_words[i]:
                    num_neg_tweets = num_neg_tweets + 1
                    neg_position_list.append(z)

        for g in range ( 0, len(pos_position_list)):
            for h in range ( 0, nSen):
                if lSen(pos_position_list(g)-1) == "n't":
                    num_neg_tweets = num_neg_tweets + 1
                    num_pos_tweets = num_pos_tweets-1

        if num_neg_tweets >= num_pos_tweets:
            print("This tweet is negative")
        else:
            print("this tweet is Positive")



def sentiment(tokenizer):
    lSen = tokenizer()
    num_pos_tweets = 0
    num_neg_tweets = 0
    pos_position_list = []
    neg_position_list = []
    nSen = len(lSen)

    positive_words = []
    with open('positive-words.txt') as inputfile:
        for line in inputfile:
            positive_words.append(line.strip())

    negative_words = []
    with open('negative-words.txt') as inputfile:
        for line in inputfile:
            positive_words.append(line.strip())

    for x in range (0, nSen):
        for i in range(0, len(positive_words)):
            if lSen[x] == positive_words[i]:
                num_pos_tweets = num_pos_tweets + 1
                pos_position_list.append(x)

    for z in range (0, nSen):
        for y in range(0, len(negative_words)):
            if lSen[z] == negative_words[i]:
                num_neg_tweets = num_neg_tweets + 1
                neg_position_list.append(z)

    for g in range ( 0, len(pos_position_list)):
        for h in range ( 0, nSen):
            if lSen(pos_position_list(g)-1) == "n't":
                num_neg_tweets = num_neg_tweets + 1
                num_pos_tweets = num_pos_tweets-1

    if num_neg_tweets >= num_pos_tweets:
        print("This tweet is negative")
    else:
        print("this tweet is Positive")


print('What is your Movie')
sUser = input()
auth = OAuthHandler(consumer_key, consumer_secret)
auth.set_access_token(access_token, access_secret)
twitterStream = Stream(auth, listener())
twitterStream.filter(track = [sUser])
print('finish')