In the development of the Stock News Scraper & Summarizer, I wanted to create a tool that would allow users to keep up with the latest news articles related to their favourite stocks. For this, I built a Python script that, when run, scrapes the latest news articles from the Yahoo Finance website and summarizing them using the NewsAPI API.

This script is designed to be run on a daily basis to provide a quick summary of the latest news articles for a given stock ticker. To accomplish this, I leveraged several key technologies:

• BeautifulSoup: This Python library was used to extract data from HTML and XML files, specifically for scraping the news articles from the Yahoo Finance website.

• NewsAPI: This API was used to search for and retrieve live articles from all over the web, providing the latest and most relevant news articles for a given stock ticker.

• Transformer: This Python library, which offers state-of-the-art Transformer models for Natural Language Processing (NLP) tasks, was used to summarize the scraped news articles​. I also used Transformers for implementing a sentiment analysis pipeline to categorise articles into «NEGATIVE» or «POSITIVE».

By providing summarized versions of the news articles, the script saves investors the time and effort of reading through each article in detail.