Scraping entire text & keywords from the webpage with help of newspaper & nltk || Python
I'm using the newspaper and nltk library for scraping, summarizing & converting articles from a webpage to a text file. Here the tokenizer "punkt" is used for splitting a phrase, sentence, paragraph, into smaller units, such as individual words or terms. #importing libraries from newspaper import Article import nltk #create tokenizer nltk.download( 'punkt' ) #input-website and create object for article url= 'https://www.marketwatch.com/' article = Article(url, language= "en" ) #downloading/parsing/npl the article article.download() article.parse() article.nlp() #printing the scraped>processed data print ( "Article Title:" ) print (article.title) #prints the title of the article print ( "\n" ) print ( "Article Text:" ) print (article.text) #prints the entire text of...