Book Image

Crafting Test-Driven Software with Python

By : Alessandro Molina
Book Image

Crafting Test-Driven Software with Python

By: Alessandro Molina

Overview of this book

Test-driven development (TDD) is a set of best practices that helps developers to build more scalable software and is used to increase the robustness of software by using automatic tests. This book shows you how to apply TDD practices effectively in Python projects. You’ll begin by learning about built-in unit tests and Mocks before covering rich frameworks like PyTest and web-based libraries such as WebTest and Robot Framework, discovering how Python allows you to embrace all modern testing practices with ease. Moving on, you’ll find out how to design tests and balance them with new feature development and learn how to create a complete test suite with PyTest. The book helps you adopt a hands-on approach to implementing TDD and associated methodologies that will have you up and running and make you more productive in no time. With the help of step-by-step explanations of essential concepts and practical examples, you’ll explore automatic tests and TDD best practices and get to grips with the methodologies and tools available in Python for creating effective and robust applications. By the end of this Python book, you will be able to write reliable test suites in Python to ensure the long-term resilience of your application using the range of libraries offered by Python for testing and development.
Table of Contents (18 chapters)
1
Section 1: Software Testing and Test-Driven Development
6
Section 2: PyTest for Python Testing
13
Section 3: Testing for the Web
16
About Packt

Using pytest-benchmark for benchmarking

Another frequent need when writing applications used by many users is to make sure that they perform in a reasonable way and, hence, that our users don't have to wait too long for something to happen. This is usually achieved by benchmarking core paths of our code base to make sure that slowdowns aren't introduced in those functions and methods. Once we have a good benchmark suite, all we have to do is rerun it on every code change and compare the results to previous runs. If nothing got slower, we are good to go.

PyTest has a pytest-benchmark plugin that makes it easy to create and run benchmarks as parts of our test suite. Like any other Python distribution, we can install pytest-benchmark through pip:

$ pip install pytest-benchmark

Once we have it installed, we can start organizing our benchmarks in their own dedicated directory. This way, they don't mix with tests, as usually we don't want to run benchmarks on every test...