Unit Testing Frameworks in Python

In this testing tutorial, you’ll read about the best Python unit test frameworks to test and correct individual units of code thus helping in overall test automation.

As the name indicates, Unit testing is a software testing method meant for testing small units of code. These are typically small, automated pieces of code written by software developers to check and ensure that the particular piece of code only behaves the way it was intended to. In Python, there are several frameworks available for this purpose and here we will discuss the major “python test automation frameworks”.

It was inspired by the Junit, a Unit Testing framework of Java programming language and if you are coming from the java background, you get hold of it easily. It is a default testing python web framework, and that’s why most developers use it for python test automation.

Unittest offers simple test execution and faster report generation. One more important plus point for this module is that it is a part of the Python coding standard library and hence no extra efforts needed to install it.  There are also certain drawbacks like it uses camelCase convention instead of snake case convention of Python

Pytest is an open-source library and pip is needed to install this. In comparison to unittest, PyTest makes the testing simple and easy with less coding. It is a general-purpose python unit test framework but used especially for functional and API testing.

Instead of several assert statements, a simple assert method is used in Pytest to reduce confusion and keep the text easy.

The Doctest module searches for docstrings to verify that all the examples work as documented in the code. It checks if all the interactive python shell examples still work as documented.

The doctest has two functions, testfile() and testmod(), we’ve used testmode() in this example which is used for a module. The test file function uses a file as documentation. The problem with doctest is that it only compares the printed output. Any variation from that will result in a test failure.

It is modelled after unittest in such a way that the tests are written for unittest will run with some minor adjustments. It is a replacement to both unittest and nose2. It has a class level setup and contains class level teardown and fixture methods. Its fixtures take a decorator-based approach thus eliminating the need for the superclass.

Nose2 can run both doctest and unittests, it is a successor to the Nose regiment. It is also called “extended unit test” pr “unittest with a plugin” because it is based upon most unit modules.

Nose2 only supports the python versions which are currently supported by python teams officially. While nose loads test lazily, nose2 loads all tests first and then begins test execution. It only supports the same level of fixtures as that of the unittest, which means only class level and module level fixtures are supported and not package level ones.

The mp plugin of nose2 enables it to run across multiple processors. This multiprocessing may speed up if the tests are heavily IO bound but it also complicates the text fixtures and can conflict with the plugins which are not designed to work with it.

We are the best python development company, as it is growing in its popularity, more and more updates are coming to existing libraries making it more simplistic and user-friendly. In my opinion, if you want to continue with python, you should focus on more pythonic libraries, as python has more about easy and well-structured syntax. Slowness in many cases is reduced by C extensions of Python libraries and that works well.

The Unit Tests provide the code more validity and ensure that the code works the way it was supposed to work. I have cleared all the basics for these 5 major testing frameworks. There is much more to learn in unit testing but I hope that this blog has provided you much the needed introduction and foundation to move forward and choose the framework as per your compatibility and requirement.

Source: https://www.zenesys.com/blog/unit-testing-frameworks-in-python

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