Testing your code, your data, and your pipelines: why software testing matters for open source and data science.
Test your work! In this Data Umbrella talk, I cover why software testing matters for open source and for data science: correctness, reliability, and contracts against future breakage. We walk through what a test looks like, how to automate tests, the kinds of tests that exist (unit, execution, integration), and how testing changes when the subject is ML model code, data validation, or pipeline code. I also share a case study from my daily work and how to navigate the tradeoff between immediate velocity and long-term productivity.