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.