from synt.utils.redis_manager import RedisManager
from synt.utils.extractors import best_word_feats
from synt.utils.text import sanitize_text

MANAGER = RedisManager()
DEFAULT_CLASSIFIER = MANAGER.load_classifier()

def guess(text, classifier=DEFAULT_CLASSIFIER):
    """Takes a blob of text and returns the sentiment and confidence score."""

    assert classifier, "Needs a classifier."
    
    bag_of_words = best_word_feats(sanitize_text(text))
    if bag_of_words:
        guess = classifier.classify(bag_of_words)
        prob = classifier.prob_classify(bag_of_words)
        return (guess, [(prob.prob(sample),sample) for sample in prob.samples()])

from synt.utils.redis_manager import RedisManager
from synt.utils.extractors import best_word_feats
from synt.utils.text import sanitize_text

MANAGER = RedisManager()
DEFAULT_CLASSIFIER = MANAGER.load_classifier()

def guess(text, classifier=DEFAULT_CLASSIFIER):
    """Takes a blob of text and returns the sentiment and confidence score."""

    assert classifier, "Needs a classifier."
    
    bag_of_words = best_word_feats(sanitize_text(text))
    if bag_of_words:
        guess = classifier.classify(bag_of_words)
        prob = classifier.prob_classify(bag_of_words)
        
        #return a -1 .. 1 score
        score = prob.prob('positive') - prob.prob('negative')
        
        return score

Return a -1 .. 1 sentiment score.
Return a -1 .. 1 sentiment score.

  from synt.utils.redis_manager import RedisManager
  from synt.utils.extractors import best_word_feats
  from synt.utils.text import sanitize_text
  
  MANAGER = RedisManager()
  DEFAULT_CLASSIFIER = MANAGER.load_classifier()
  
  def guess(text, classifier=DEFAULT_CLASSIFIER):
      """Takes a blob of text and returns the sentiment and confidence score."""
  
      assert classifier, "Needs a classifier."
      
      bag_of_words = best_word_feats(sanitize_text(text))
      if bag_of_words:
          guess = classifier.classify(bag_of_words)
          prob = classifier.prob_classify(bag_of_words)
-         return (guess, [(prob.prob(sample),sample) for sample in prob.samples()])
+         
+         #return a -1 .. 1 score
+         score = prob.prob('positive') - prob.prob('negative')
+         
+         return score
  
Return a -1 .. 1 sentiment score.
## Code Before:
from synt.utils.redis_manager import RedisManager
from synt.utils.extractors import best_word_feats
from synt.utils.text import sanitize_text

MANAGER = RedisManager()
DEFAULT_CLASSIFIER = MANAGER.load_classifier()

def guess(text, classifier=DEFAULT_CLASSIFIER):
    """Takes a blob of text and returns the sentiment and confidence score."""

    assert classifier, "Needs a classifier."
    
    bag_of_words = best_word_feats(sanitize_text(text))
    if bag_of_words:
        guess = classifier.classify(bag_of_words)
        prob = classifier.prob_classify(bag_of_words)
        return (guess, [(prob.prob(sample),sample) for sample in prob.samples()])

## Instruction:
Return a -1 .. 1 sentiment score.
## Code After:
from synt.utils.redis_manager import RedisManager
from synt.utils.extractors import best_word_feats
from synt.utils.text import sanitize_text

MANAGER = RedisManager()
DEFAULT_CLASSIFIER = MANAGER.load_classifier()

def guess(text, classifier=DEFAULT_CLASSIFIER):
    """Takes a blob of text and returns the sentiment and confidence score."""

    assert classifier, "Needs a classifier."
    
    bag_of_words = best_word_feats(sanitize_text(text))
    if bag_of_words:
        guess = classifier.classify(bag_of_words)
        prob = classifier.prob_classify(bag_of_words)
        
        #return a -1 .. 1 score
        score = prob.prob('positive') - prob.prob('negative')
        
        return score
