What volume of data have you had to process in your projects?

The volume of data handled in Python projects varies greatly depending on the task and infrastructure. For example:

• In small web applications — a few megabytes or gigabytes of data stored in databases.
• In data analysis projects — from gigabytes to terabytes, often using libraries like pandas, NumPy, and big data tools.
• In machine learning systems — hundreds of megabytes to tens of terabytes, including training datasets and models.

It is important to be able to optimize data processing using streaming, databases, distributed computing, and efficient data structures.