Description
Tests can be helpful: they can find bugs in new code, check for regressions in old code, and clarify precisely what the code is meant to do. On the other hand, writing tests is often tedious - and it's rare to think of an error when testing that you forgot when writing the code. Even worse, as scientists we write code because we don't yet know the correct answer - so how can we possibly test it? The answer is to generate many inputs, and check whether the code does something _wrong_, like changing the data you save-then-load. Whether you're a novice Pythonista or gnarled wizard, this Talk about property-based testing with Hypothesis will educate, entertain, and help take your testing to the next level.