What is the best unit testing framework for Python?

Unit testing is a software testing method where individual units of code are tested. Software developers write these small, automated pieces of code to ensure and verify that the particular piece of code known as the unit behaves as it is expected to.

To achieve this specific purpose, there are python unit testing frameworks that can be leveraged. This framework provides a streamlined structure to carry out the testing activities rewardingly.

In this article, you will get to know the best unit testing frameworks for python.

What is python?

It is a high-level, interpreted, general programming language that helps programmers to write logical and manageable code for large-scale as well as small-scale projects. It can be debugged easily and provides an extensive support library.

What is python testing?

Python comes will libraries and tools that truly support automated testing. It is easy to write python test cases. With the rising demand for python, python-based test automation frameworks are also proving to be effective.

The following are the best python unit testing frameworks:

1. Unittest: It is built based on the functionality of JUnit. It is considered to be a default testing framework for most developers using the test automation platform.

Certain test cases can be skipped by this framework if certain conditions are not in line with the skip() decorator.

Faster report generation and simple test execution are offered by this framework. It is a part of the Python coding standard library and hence can be installed easily.

2. Pytest: Pip is required to install this framework and it is an open-source library. The testing process can be easily done and that too with less coding.

It is a general-purpose python unit test framework and is especially used for both API and functional testing. In order to keep the text easy, a simple assert method is used in Pytest.

When reliable input context for the tests needs to be provided consistently then fixtures can be used. The function syntax is used for fixtures.

3. Doctest: This python unit testing framework is used for searching all the docstrings, so that all the examples are verified to ascertain they work as documented in the code.

All the interactive python shell examples are checked to know if it still works as documented. Testfile() and testmod() are the two functions of doctest.

4. Testify: It is built keeping unittest as the base framework, wherein tests that are written for unittests will run with only a few minor adjustments. It has a class-level setup wherein fixture methods and class-level teardown are contained.

A decorator-based approach is used by its fixtures so that the need for the superclass is eliminated.

5. Nose2: This python unit testing framework can run on both unittests and doctest and it is a successor to doctest. It is also called as a “unittest with a plugin” or “extended unit test” because it is based upon unit modules.

The official python versions that are currently supported by python teams are used by Nose2.

All tests are first loaded by Nose2 and then test execution is initiated. The same level of fixtures is supported as that of the unittest, which means, only module-level and class-level modules are supported. Nose2 can run across multiple processors using the mp plugin.

Conclusion: If you are looking forward to implementing unit testing for your specific project, then do get connected with a well-established software testing services company that will provide you with a well-defined testing framework that is in line with your project specific requirements.

About the author: I am a technical content writer focused on writing technology specific articles. I strive to provide well-researched information on the leading market savvy technologies.