You've heard the gospel of 'test, test, test!' over and over again, and may have even felt some jealousy or guilt because you're not using Test-Driven Development. Maybe you've even seen talks or read blog posts about writing 'testable code', but it just hasn't sunk in.
The reality is that writing effective unit tests can be somewhat difficult to wrap your head around. What's a unit test? When is a unit test not a unit test? What's a functional test? When is a Mock really a fake or stub? There's a good bit of lingo, a fair amount of religion, but not enough instruction on effective testing patterns and idiomatic, Pythonic testing practices.
As programming and application architecture is heavily influenced by the use of patterns, it's only logical that those patterns produce the side effect of making the way they'll be tested more predictable, and yet discussions of patterns regularly leave out coverage of testing, and most testing talks fail to link a methodology to patterns in the code. This changes now.
In this talk, aimed at intermediate Pythonistas, we'll have a look at some common, simple patterns in code, and then have a look at the testing patterns that go with them. We'll also discover what makes some code more testable than others, and how mocks and fakes can help truly isolate the code to be tested (and why you really want to do that). Finally, we'll touch on some tools to help make writing and running tests easier.