Do you spend a lot of time on maintaining your mocks? Has your test suite passed and your code failed to run in production? This could be a result of using mocks too aggressively or not utilising safety features provided by Python’s mock library. In this post, we will explore the benefits and potential risks of using mocks, discuss strategies for designing high-level interfaces that are safe to mock, and examine a linter tool that ensures safe mock usage. Let’s begin by examining the potential risks associated with using mocks.

Continue reading “Navigating Mocks in Python: Strategies for Safe and Efficient Mock Usage” →