Real-Time Stock Market Data Scraper

Project Overview

Developed a Python script for scraping real-time stock market data from financial websites, enabling quick access to stock prices, market trends, and financial news.

Technical Challenges

High Frequency Updates: Dealing with the rapid update rates of stock prices and market data.

Complex Data Structures: Extracting data from complex and dynamically changing web pages of financial markets.

Solutions Implemented

Efficient Scraping Techniques: Used libraries such as BeautifulSoup for parsing HTML and Selenium for interacting with JavaScript-driven pages.

Continuous Data Streaming: Implemented websocket connections where available to receive real-time data updates directly from stock exchange feeds.

Project Outcome

The script provides users with immediate access to the latest stock market information, enhancing trading strategies and decision-making processes.

Technologies Used

Languages: Python

Libraries: Selenium, BeautifulSoup, Websockets