This project introduces advanced usage of Python generators to efficiently handle large datasets, process data in batches, and simulate real-world scenarios involving live updates and memory-efficient computations. The tasks focus on leveraging Python’s yield keyword to implement generators that provide iterative access to data, promoting optimal resource utilization, and improving performance in data-driven applications.
Learning Objectives By completing this project, you will:
Master Python Generators: Learn to create and utilize generators for iterative data processing, enabling memory-efficient operations. Handle Large Datasets: Implement batch processing and lazy loading to work with extensive datasets without overloading memory. Simulate Real-world Scenarios: Develop solutions to simulate live data updates and apply them to streaming contexts. Optimize Performance: Use generators to calculate aggregate functions like averages on large datasets, minimizing memory consumption. Apply SQL Knowledge: Use SQL queries to fetch data dynamically, integrating Python with databases for robust data management