Idempotency is an important concept in data engineering, particularly when working with distributed systems or databases. In simple terms, an operation is said to be idempotent if running it multiple times has the same effect as running it once. This can be incredibly useful when dealing with unpredictable network conditions, errors, or other types of unexpected behavior, as it ensures that even if something goes wrong, the system can be brought back to a consistent state by simply running the operation again.

In this blog post, we will take a look at some examples of how idempotency can be achieved in data engineering using Python.