Automated Web Scraping Tool

Web data extraction, also known as web scraping, is a powerful technique used to extract data from websites using their HTML structure. Web scraping can be useful in a variety of industries, such as marketing, finance, and research, as it allows businesses and researchers to gather large amounts of data quickly and efficiently. Python is a popular programming language for web scraping due to its flexibility and ease of use. The two libraries that are commonly used in Python for web scraping are Beautifulsoup and requests. Requests is a Python library used to send HTTP requests to web pages, and it returns the server’s response as an HTTP response object. This library can be used to obtain HTML pages from websites, which can then be analyzed or processed by other Python libraries such as Beautifulsoup. Beautifulsoup is a Python library that parses HTML and XML documents and extracts data from them. With Beautifulsoup, you can locate and extract specific HTML tags or attributes from a webpage, and retrieve their contents or values. Beautifulsoup provides a convenient way to navigate and search through complex HTML documents, making it an essential tool for web scraping with Python. We first import the requests and Beautifulsoup libraries. We then define the URL to scrape and send an HTTP request to that URL using the requests library. We use the Beautifulsoup library to parse the HTML content of the response and extract the page title and all links on the page. Finally, we print the title and links to the console. The overall main objective of this project is to extract information from website and process it into simple structures such as spreadsheets, database or CSV file.