Building unit test functions for ETL pipelines
In this recipe, we will learn how to build some unit test functions for your ETL pipeline to help identify and fix issues at an early stage of your pipeline development. By incorporating unit tests, you can catch errors early in the development process, leading to more robust and reliable data workflows. This recipe is particularly useful for data engineers who need to validate the functionality of their ETL jobs and ensure data integrity before deploying them to production.
The goal of this recipe is to introduce some code snippets of functions to test Glue Jobs in a unit testing context that you can use to integrate into your Glue pipeline or your company’s internal libraries.
How to do it…
- You should create a file name, such as
unit_test.py
, that is separate from your ETL code. This file will contain various functions for unit testing. - Import the relevant libraries. These are the libraries that we will...