TextBlob: Processing Text in One Line of Code

To quickly analyze text, including determining its sentiment, tokenization, noun phrase and word frequency analysis, and spelling correction, use TextBlob.

To use TextBlob, start with creating a new instance of the TextBlob class with the text “Today is a beautiful day”.

from textblob import TextBlob

text = "Today is a beautiful day"
blob = TextBlob(text)

Tokenize words:

blob.words

WordList(['Today', 'is', 'a', 'beautiful', 'day'])

Extract noun phrases:

blob.noun_phrases

WordList(['beautiful day'])

Analyze sentiment:

blob.sentiment

Sentiment(polarity=0.85, subjectivity=1.0)

Count words:

blob.word_counts

defaultdict(int, {'today': 1, 'is': 1, 'a': 1, 'beautiful': 1, 'day': 1})

Correct spelling:

text = "Today is a beutiful day"
blob = TextBlob(text)
blob.correct()

TextBlob("Today is a beautiful day")

Link to TextBlob.

Run in Google Colab.