Python: Automated testing

Included in the course

What you'll learn

• Write high-quality code with fewer bugs
• Build your code architecture so that users are comfortable
• Automatically review code and work faster
• Refactor more often with the assurance that testing provides

Description

This course introduces you to the principles and tools of automated testing in Python. You will learn to write automated tests, measure coverage, and set continuous integration. The skills you learn in this course will help you improve the quality of your code. You'll be able to create a code architecture that is easy to use. Completing a course on environment and feature preparation is a wise idea to make learning easier.

Course program

• 1

  Introduction

  Getting to know the course topic

  theory
• 2

  Testing objectives

  Understanding what testing does

  theory
• 3

  Assertions

  Learning about assert, the built-in statement in Python

  theory
• 4

  Pytest framework

  Exploring the most popular testing framework in Python

  theory
• 5

  Modular tests

  Learning to write, using the stack test as an example

  theory
• 6

  Data preparation

  Exploring the Pytest facilities

  theory
• 7

  Bad and good testing practices

  Exploring the most common mistakes in writing tests

  theory
• 8

  Testing through documentation

  Finding out how tests work through documentation

  theory
• 9

  Covering the code with tests

  Learning to find code that is not affected by tests

  theory
• 10

  Development through testing

  Learning to write tests before writing the code

  theory
• 11

  Continuous integration

  Learning about automatic project assembly

  theory
• 12

  Conclusion

  Summarizing the course topic

  theory
• 13

  Additional resources

  Some materials the Hexlet team have picked up. This will give you a more in-depth understanding of the topic