spaCyTextBlob

Easy sentiment analysis for spaCy using TextBlob. Now supports spaCy 3.0!

Installation

First install spacytextblob from PyPi


  pip install spacytextblob                                                     
  

TextBlob requires some data to be downloaded before getting started.


  python -m textblob.download_corpora
  

spaCy requires that you download a model to get started.


  python -m spacy download en_core_web_sm
  

Quick start

First add spaCyTextBlob to the spaCy pipeline


  >>> import spacy
  >>> from spacytextblob.spacytextblob import SpacyTextBlob
  >>>
  >>> nlp = spacy.load('en_core_web_sm')
  >>> nlp.add_pipe("spacytextblob")
  >>>
  >>> # pipeline contains component name
  >>> print(nlp.pipe_names)
  ['tok2vec', 'tagger', 'parser', 'ner', 'attribute_ruler', 'lemmatizer', 'spacytextblob']
  

Then run text through the nlp pipeline as you normally would


  >>> text = "I had a really horrible day. It was the worst day ever!" 
  >>> doc = nlp(text) 
  >>> print('Polarity:', doc._.polarity) 
  Polarity: -1.0
  >>> print('Subjectivity:', doc._.subjectivity) 
  Subjectivity: 1.0
  >>> print('Assessments:', doc._.assessments) 
  Assessments: [(['really', 'horrible'], -1.0, 1.0, None), (['worst', '!'], -1.0, 1.0, None)]