aiobp

Create a fully-functional asynchronous web scraper using the Python package 'aiobp'. This application will scrape multiple websites concurrently to gather data on real-time stock prices from various financial platforms. The goal is to demonstrate the power of asynchronous programming with 'aiobp' to efficiently handle I/O-bound tasks such as web scraping.

### Step-by-Step Guide:
1. **Setup**: Initialize your project environment and install the required packages including 'aiobp', 'aiohttp' for making HTTP requests, and 'beautifulsoup4' for parsing HTML content.
2. **Configuration**: Define the URLs of the financial websites you want to scrape and configure 'aiobp' to manage these requests asynchronously.
3. **Scraping Logic**: Implement the logic within 'aiobp' to scrape each website for stock price information. Ensure that the scraping process respects the website's terms of service and does not overload their servers.
4. **Data Processing**: Once the data is scraped, process it to extract relevant stock price details such as company name, current price, and change percentage.
5. **Output**: Display the processed data in a user-friendly format, either on the console or via a simple web interface using Flask or FastAPI.
6. **Testing**: Thoroughly test the application to ensure it works correctly under different conditions, such as varying network speeds and server responses.
7. **Optimization**: Optimize the application for performance, ensuring efficient use of resources and minimal latency.

### Suggested Features:
- **Real-Time Updates**: Implement functionality to periodically update stock prices every minute or so without restarting the application.
- **Error Handling**: Add robust error handling to deal with potential issues like connection timeouts or failed requests.
- **Logging**: Integrate logging to keep track of operations and errors.
- **User Interface**: Develop a simple web interface where users can input a ticker symbol and receive real-time stock price information.
- **Database Integration**: Store historical stock price data in a database for later analysis.

### Utilizing 'aiobp':
- Use 'aiobp' to set up an async service that handles the concurrent execution of HTTP requests to the specified URLs.
- Leverage 'aiobp' decorators to define async functions for scraping and processing data.
- Take advantage of 'aiobp' event loops and task management features to efficiently schedule and execute tasks.