Professional Testing with Python¶

What Participants Say About This Course¶

I think overall the course was held excellently. I learnt a lot and learnt how to use the different techniques and ideas.

—Vinay Mathew, course participant

Great opportunity to learn directly from the author of py.test.

—a course participant

Impressive & abundant, clear information. It’s been a privilege!

—a course participant

Target Audience¶

People with a Python programming background, interested in best practices of testing Python libraries and applications. This course can be combined with introductory courses (see Recommended Module Combinations) to achieve appropriate Python skills.

Motivation¶

Testing is essential for code quality. Tests need to be automated and regularly run to benefit from them. Frameworks such as pytest are based on many years of exercise and help you apply best practices to your tests. Apart from integrating with existing unittest/nose test suites, pytest offers some unique features for writing and organizing your test code.

Testing and releasing your code for many different Python versions and implementations can be hard. The tox project is an effective tool to integrate testing and deployment. It works with and connects to established tools including those for Continuous Integration.

Applying the Python philosophy that simple things should be simple and complex tasks should be possible, pytest and tox make it easy to get started but at the same time provide powerful features for professional software development.

Course Content¶

In distinct steps we introduce terms and tools for testing in Python. Each step consists of an input, discussion and self-practice phase.

The main topics of the course are:

• About testing: Why and how to write tests

• About pytest: Why pytest, popularity, history overview

• The basics: Fundamental pytest features, test discovery and plain asserts

• Configuration: Typical directory structure, configs, options

• Marks: Marking/grouping tests, skipping tests

• Parametrization: Running tests against sets of input/output data

• Fixtures: Providing test data, setting up objects, modularity

• Built-in fixtures: Temporary files, patching, capturing output, test information

• Fixtures advanced: Caching, cleanup/teardown, implicit fixtures, parametrizing

• Migrating to pytest: Running existing testsuites, incremental rewriting, tooling

• Mocking: Dealing with dependencies which are in our way, alternatives, monkeypatch and unittest.mock, mocking libraries and helpers

• Plugin tour: Coverage, distributed testing, output improvements, alternative test syntax, testing C libraries, plugin overview

• Property-based testing: Using hypothesis to generate test data

• Writing plugins: Extending pytest via custom hooks, domain-specific languages

• Open space: Discussions of your choice, postponed issues from the course

Course Style¶

This is a hands-on course with lots of student activities. The presentation parts are usually short and include real-life examples. Students will create their own tests from the very beginning. Exercises are an important part of the training. Students are encouraged to bring their own problems to be discussed during the course.

Exercises¶

The participants can follow all steps directly on their computers. There are exercises at the end of each unit providing ample opportunity to apply the freshly learned knowledge.

Software¶

We use our online programing system that contains all needed software. There is no need to install any additional software. A modern internet browser and a decent internet connection will be enough.

Hardware for Open In-Person Trainings¶

For open trainings at our teaching center you can use your own laptop. Alternatively, we provide teaching computers. Please let us know if you need one in your registration form.

Course Material¶

Every participant receives comprehensive materials in PDF format that cover the whole course content as well as all source code.

Recommended Module Combinations¶

You should have intermediate Python experience or attend the course Python for Programmers before. You might be also interested in the course Advanced Python.