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Pytest for testing Flowkit components

Date: 20 July 2018




Testing is an important component of a fast changing software. Without testing it is not possible to guarantee that new components or changes to the current codebase do not break pre-existing functionality. The purpose of unit testing in particular is to ensure that isolated parts of the codebase work as expected by the developer. Tests should provide enough evidence to the developer that his contributions are working. It also aids other developers to understand the purpose of each and every component.

In order to reduce the burden of writing tests, we need good test management tools that play well with python which is the main scripting language for this project.

There are many testing framework for Python, including: nosetests, unittest and pytest.

We were previously using nosetests, which makes use of classic xunit-style setup whose main strength is easily declaring setup and teardown methods for each testing function. While these methods are simple and familiar to those coming from a unittest or nose background, pytest’s more powerful fixture mechanism leverages the concept of dependency injection, allowing for a more modular and more scalable approach for managing test state, especially for larger projects and for functional testing.

In our particular case, we can leverage the power of fixtures to manage docker images and to define connection procedures. Ideally, all of the testing requirements are defined within the testing framework. Fixtures are really powerful in providing powerful abstractions for resource allocation.


We will use pytest for testing Flowkit components.


All of the tests should be written in compliance with pytest. We should leverage fixtures to define resource allocation and key abstractions reducing the burden of writting tests as much as possible.

Given that most of our development are expected to be in python, we can take full advantage of pytest.