Handle massive datasets without breaking your memory. This project teaches you to use Python generators for efficient data processing and real-world streaming scenarios.
- Memory-efficient data processors using
yield - Batch processing systems for huge datasets
- Live data streaming simulations
- SQL-integrated data pipelines
- Python 3.x
- Basic SQL (MySQL/SQLite)
- Git basics
Loading a 10GB dataset into memory? Your system will crash. Generators let you process data one piece at a time, keeping memory usage flat no matter how big your data gets.
git clone <repo-url>
cd python-generators-project
pip install mysql-connector-python python-dotenvSet up your database, then run the examples to see generators crush large datasets with minimal resources.
Data engineers, backend devs, or anyone tired of "out of memory" errors when processing real-world data.