Python text analyzer using TextBlob and Textatistic.

language_analyzer.py

import nltk
from textblob import TextBlob
from textblob.sentiments import NaiveBayesAnalyzer
from textatistic import Textatistic

# This corpus is required for the Naive Bayes Analyzer
nltk.download("movie_reviews")

def main():
    user_text = get_user_text()
    blob = convert_to_blob(user_text)
    texta_dict = convert_to_textatistic_dict(user_text)
    print()
    display_sentiment(blob)
    print()
    display_basic_stats(texta_dict)
    print()
    display_readability(texta_dict)

def get_user_text():
    user_text = input("Copy and paste the text you would like to analyze below:\n")
    return user_text

def convert_to_blob(text):
    blob = TextBlob(text, analyzer=NaiveBayesAnalyzer())
    return blob.sentiment

def convert_to_textatistic_dict(text):
    return Textatistic(text).dict()

def display_sentiment(blob):
    """Uses the Naive Bayes Anaylzer corpus to measure
    a text's positive percentage, negative percentage, and
    the text's overall classification, where 'pos' is
    positive and 'neg' is negative."""
    
    print("Sentiment Summary:\n".upper())
    print(f"Positive percentage: {round(blob.p_pos * 100, 2)}%")
    print(f"Negative percentage: {round(blob.p_neg * 100, 2)}%")
    print(f"Overall sentiment classification: {blob.classification}")

def display_basic_stats(texta_dict):
    """Pulls from a Textatistic dictionary to diplays character count,
    word count, sentence count, and number of polysyllable words."""
    
    print("Basic Stats:\n".upper())
    print(f"Character count: {texta_dict['char_count']}")
    print(f"Word count: {texta_dict['word_count']}")
    print(f"Sentence count: {texta_dict['sent_count']}")
    print(f"Polysyllable words used: {texta_dict['polysyblword_count']}")

def display_readability(texta_dict):
    """Flesh Kincaid score corresponds to a specific grade level.
    Gunning Fog score corresponds to a specific grade level.
    SMOG score corresponds to the years of education required to understand a text.
    Dale-Chall score maps to grade levels from 4 and below to college grads (grade 16) and above."""
    
    print("Readability Summary:\n".upper())
    print(f"Flesch Kincaid score: {round(texta_dict['fleschkincaid_score'], 1)}")
    print(f"Gunning Fog score: {round(texta_dict['gunningfog_score'], 1)}")
    print(f"Simple Measure of Gobbledygook score: {round(texta_dict['smog_score'], 1)}")
    print(f"Dale-Chall score: {round(texta_dict['dalechall_score'], 1)}")

if __name__ == "__main__":
    main()