Python keyword generator function

To create an SEO keyword generator function in Python, we'll need to use some natural language processing techniques to extract relevant keywords from the input text. In this case, we'll use the Natural Language Toolkit (NLTK) library for text processing. Additionally, we'll integrate this function into a Django web application to receive input text from users and display the generated keywords.

First, make sure you have Django and NLTK installed. You can install them using pip:

pip install Django nltk

              
                # keyword_generator/utils.py
import nltk
from nltk.corpus import stopwords
from nltk.tokenize import word_tokenize
from nltk.stem import PorterStemmer

nltk.download('punkt')
nltk.download('stopwords')

def generate_keywords(text):
    # Tokenize the text into words
    words = word_tokenize(text)

    # Remove stopwords (common words like "the", "is", "and", etc.)
    stop_words = set(stopwords.words('english'))
    words = [word.lower() for word in words if word.lower() not in stop_words]

    # Stemming the words (converting words to their root form)
    stemmer = PorterStemmer()
    stemmed_words = [stemmer.stem(word) for word in words]

    # Count word frequencies
    word_freq = {}
    for word in stemmed_words:
        word_freq[word] = word_freq.get(word, 0) + 1

    # Sort the words by frequency in descending order
    sorted_words = sorted(word_freq.items(), key=lambda x: x[1], reverse=True)

    # Return the top 10 keywords (you can adjust this number as needed)
    return [word for word, _ in sorted_words[:10]]