analyzer

import nltk
import sys
write = sys.stdout.write

class Analyzer():
    """Implements sentiment analysis."""


    def __init__(self, positives, negatives):
        """Initialize Analyzer."""
        self.positives = []
        self.negatives = []

       	with open(positives) as infile:
           for line in infile:
               if not line.startswith((';', ' ')):
                   self.positives.append(line)

        with open(negatives) as infile:
           for line in infile:
               if not line.startswith((';', ' ')):
                   self.negatives.append(line)





    def analyze(self, text):
        """Analyze text for sentiment, returning its score."""
        #scores: positive = 1, negative = -1, neutral = 0
        score = 0

        #instantiate tokenizer
        tokenizer = nltk.tokenize.TweetTokenizer
        tokens = tokenizer.tokenize(text)

        #iterate over tokenized tweets
        for token in tokens:
            token = token.lower()

        #check if word is pos or neg (if text is in self.positives or self.negatives )
        if token in self.positives:
            score += 1

        elif token in self.negatives:
            score -= 1

     	return score