Python-Based Web Scraping Tool for Real-Time Weather and News Information Extraction and Analysis
DOI:
https://doi.org/10.51699/cajmtcs.v7i4.989Keywords:
Web Scraping Tool, Real-Time Information Collection, Decision-Making, Analysis, Prediction, User-Friendly, Beautiful Soup ParsesAbstract
This project presents a Python-based web scraping tool that can automatically extract real-time weather information and news headlines from various internet sources. This tool makes that easy by bringing all the info together in one place, so you don’t have to go looking. The system can efficiently collect and organise data using Python libraries like requests, Beautiful Soup and pandas. The requests library is used to get the content of web pages and Beautiful Soup is used to parse and extract useful information like temperature, humidity, wind speed and weather conditions from weather websites and top headlines and brief descriptions from popular news portals. The scraped data is cleaned, structured and presented in a user-friendly format which is easy to interpret and analyse. This guarantees users accurate, nicely formatted results that can be stored or further processed for other applications. To summarise, this project demonstrates the usefulness of web scraping as an effective way to automate data collection and deliver real-time information in a timely fashion. The weather and news extraction tool is a perfect solution for everyday information retrieval, taking advantage of the simplicity of Python and the extensive library support. It reduces manual work, makes things more affordable and serves as the basis for creating more sophisticated systems that leverage real-time data to analyse, predict and decide.
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