class_docstr: Sentiment analyzer that uses the same implementation as the
  pattern library. Returns results as a named tuple of the form:
  
  ``Sentiment(polarity, subjectivity, [assessments])``
  
  where [assessments] is a list of the assessed tokens and their
  polarity and subjectivity scores
docstr: Return the sentiment as a named tuple of the form:
  ``Sentiment(polarity, subjectivity, [assessments])``.
docstr_tok: ["Return","the","sentiment","as","a","named","tuple","of","the","form",":","``","Sentiment","(","polarity",",","subjectivity",",","[","assessments","]",")","``","."]
code: def analyze(self, text, keep_assessments=False):
      """Return the sentiment as a named tuple of the form:
      ``Sentiment(polarity, subjectivity, [assessments])``.
      """
      #: Return type declaration
      if keep_assessments:
          Sentiment = namedtuple(
              "Sentiment", ["polarity", "subjectivity", "assessments"]
          )
          assessments = pattern_sentiment(text).assessments
          polarity, subjectivity = pattern_sentiment(text)
          return Sentiment(polarity, subjectivity, assessments)
  
      else:
          Sentiment = namedtuple(
              "Sentiment", ["polarity", "subjectivity"]
          )
          return Sentiment(*pattern_sentiment(text))
  
file_path: TextBlob/textblob/en/sentiments.py
imports: from __future__ import absolute_import
  from collections import namedtuple
  import nltk
  from textblob.en import sentiment
  from textblob.tokenizers import word_tokenize
  from textblob.decorators import requires_nltk_corpus
  from textblob.base import BaseSentimentAnalyzer, DISCRETE, CONTINUOUS
label_desc: Use image node_id 1 for calling the PatternAnalyzer obj's underlying member method code with example usage: obj.analyze(text, keep_assessments) and returns: Sentiment, Sentiment