0:00 - Introduction
1:08 - What is unit testing
2:06 - Benefits of unit testing
3:28 - So why doesn't everyone write unit tests?
5:26 - Patterns in Data Science
6:15 - Where to start
9:08 - How do we actually write tests. Introduction to Pytest Framework
10:03 - First unit test example
12:08 - Fixtures. Modular approach to setup and teardown methods
16:08 - Useful built-in fixtures, capsys
18:12 - Flexibility of fixtures
22:12 - Mocks
24:25 - Test with Mock
26:35 - Mock objects
29:29 - MagicMock objects in the REPL
30:05 - Actions taken by mock object
31:01 - Mock object side effect method
33:54 - Assertions on mock objects
35:24 - Be wary of assertion typos
36:49 - Gotchas for mocks
38:37 - Helpful libraries
38:44 - Useful blog posts
38:55 - Link to github repository + Conclusion
video url: https://www.youtube.com/watch?v=TPKgpzm4LZ8
Contents
0:00 - Introduction 1:08 - What is unit testing 2:06 - Benefits of unit testing 3:28 - So why doesn't everyone write unit tests? 5:26 - Patterns in Data Science 6:15 - Where to start 9:08 - How do we actually write tests. Introduction to Pytest Framework 10:03 - First unit test example 12:08 - Fixtures. Modular approach to setup and teardown methods 16:08 - Useful built-in fixtures, capsys 18:12 - Flexibility of fixtures 22:12 - Mocks 24:25 - Test with Mock 26:35 - Mock objects 29:29 - MagicMock objects in the REPL 30:05 - Actions taken by mock object 31:01 - Mock object side effect method 33:54 - Assertions on mock objects 35:24 - Be wary of assertion typos 36:49 - Gotchas for mocks 38:37 - Helpful libraries 38:44 - Useful blog posts 38:55 - Link to github repository + Conclusion