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Post By Admin Last Updated At 2021-05-29
Best Python Testing frameworks useful in 2021

Testing software means verifying software that runs correctly based on given inputs and locates the bugs that need to be fixed. It is impossible for a person or a team handling a project to cope up with all the important updates and interactions between the changes. Thus, automated testing is the only option to build reliable and secure software on the go. In this regard, Python helps very much as it comes with various tools and in-built libraries. These tools and libraries are much useful to build automation tests for the apps. Therefore, Python testing came into existence and it offers very smooth processes to test apps automatically. 

Moreover, with the expansion of AI applications, Python became a more popular and the top coding language of this era. It is not possible to say whether the software works properly without initiating a test. Besides, this testing solution has two sides, either manual or automatic. Most companies today prefer automation testing only to save precious time and overhead costs. Python testing is so famous to determine the correctness of the software. Because this is a dynamically typed coding language with simple and understandable syntax. 

Further, Python test cases are also easy to write without putting much effort into codes. Python is a very simple language and provides an easy-to-understand syntax for developers and users. Thus, most developers prefer to use it for testing software and in many other solutions. 

In this blog, we will discuss how Python testing is useful and the top Python testing tools useful in 2021. 

Python testing tools 

There are numerous Python testing tools within the testing language ecosystem. Hence, Python-based automation testing tools are slowly becoming famous. These are-

Robot

Unittest

DocTest

Pytest

Nose2

Testify

Let us elaborate on these Python testing tools in detail.

Python testing frameworks

Robot

The robot is an open-source most popular Python testing library under acceptance testing. Moreover, this framework is completely python-based and useful for test-driven development and acceptance testing. Under this framework, the “keyword style” is used to write the test cases. It supports running the platforms like Java and Dot Net along with it supports cross-platform automation testing for Windows, macOS, etc. Moreover, it supports Linux OS for desktop apps, mobile apps, and web apps. Hence, the robot framework is also useful for RPA along with Acceptance testing.

In order to install Robot, it is suggestible to use the PiP package. Further, there are some strong features of Robot like keyword-driven testing, tabular-data syntax, rich libraries, etc make it popular among testers. 

The important features of the Robot framework are as follows:-

It comes in a simple tabular format that is useful for writing test cases with keywords.

Also, the robot framework comes with built-in keywords available with the Selenium libraries. 

It also supports various libraries and variables. 

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UnitTest

This is the foremost python testing framework designed to work with Python standard library performing automated tests. Also, it best supports the reuse of test suits and test arrangements. Moreover, it supports automation testing inspired by JUnit and test collections, setup code for conducting tests, etc. This unit test is also known as PyUnit. Additionally, some new features are added to the Unittest2, is a backport or the latest version. 

The standard workflow of this python testing framework are-

Import the Unittest module within the program code and users can define their own class. Then users can build functions within the defined class. 

Later place the function unittest.main() at the last of the code which is the main method of Python testing to run the test case. Moreover, the unit test verifies a small component within the user application. 

It allows the programmer to refactor the code later making sure the modules working perfectly. 

Due to the modular nature of this framework, users can test various parts of the project without waiting for others to complete it. 

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PyTest

PyTest is a free-to-use Python testing framework useful for all-purpose but mainly for functional testing and API testing. To install Pytest it requires PiP or python package installer. Moreover, PyTest supports either simple or complex text code that is useful for testing user interfaces, DBs, and APIs. Besides, Python uses a simple syntax to execute tests in a simple way. It uses very rich plugins and also able to run multiple tests parallelly. The most valuable features of the PyTest tool includes the following:-

It is an open-source automation Python Testing framework having simple syntax and easy to start.

This framework has built-in support for test discovery.

Also, it has CLI (Command-Line) support.

This Python framework has the extensibility of rich plugins and hooks.

Also, it has large community support and it works with its popular in-built unit tests.

It automatically locates the tests with a particular filename “checks”.

The Pytest framework is easy to get started by creating tests.

Moreover, Pytest supports parameterization and these tests look very clear having large data sets.

Besides, it supports various fixtures that are types of functions that run before each test function.

DocTest

DocTest is nothing but the two different sections of a productive software expansion process. These are documentation and testing which are the core components of this process. This is a simple module cum testing method useful for python programs mainly for white-box unit testing. These tests don’t need individual scripts to write test cases that to in comparison with unit tests. Besides, it makes the search for the interactive Python sessions and verifies whether they working as per requirement. Also, it uses certain Python capabilities known as Docstrings. 

The core functions of the Doctest python testing framework are- updating the docstring and conducting regression testing. This framework uses the below Python capabilities such as - docstrings, the python interactive shell, and Python introspection.  Also, this is a good and better option for small tests. 

Nose2

Nose2 is the next generation of the Nose framework and the python-based unit testing tool in Python testing. Moreover, it has the capability to run DocTest and unit tests easily. This python framework is based on Unittest and considered as extended unittest, Further, it uses a simple plugin design that makes the testing process easier and simple. It also supports different test functions useful for writing tests and exceptions smoothly. 

This Nose2 framework also supports package fixtures, classes, modules, etc to be defined at a single time rather than writing regularly. 

Also, this Python testing tool takes PyUnit (testing framework of Python) a step ahead through supporting automatic test discovery. It uses certain plugins for test execution and document collection. There is a DSL called Such that used by Nose2 for writing various functional tests easily. The most useful features of nose2 are as follows:-

It is a popular test runner within Python coding that helps to detect unit tests within the user project and executes them. 

This framework is based on another Python framework Unittest and adds more value to it through its rich plugins. 

It also provides better plugin APIs and simplifies the internal interfaces and other useful processes.

Moreover, Nose2 supports various types of parameterization and generator tests than the Nose framework.

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Testify

This Python testing tool is designed to replace the two other test frameworks- UnitTest and Nose. Because this framework has extra and advanced features than Unittest. Moreover, this testing framework is as popular as the Java implementation of semantic testing. Therefore, automated unit testing, integration testing, and system testing are easier for this Python framework. 

The features of the Testify testing tool includes the following:-

It uses simple syntax for the fixture method. 

Also, it has a devised test discovery feature.

This Python framework has an extensible plugging system. 

Moreover, the testing utilities are also easier and simple with this framework.

The test components are simple, reusable, and manageable. 

Other than the above there are some additional Python testing frameworks. 

It is easy to add additional test features to this testing tool.

Behave

It is also called BDD a python testing framework useful for black-box testing. This testing framework works mainly with Unicode Strings and uses NLP or natural language for writing tests. Moreover, the directory of this framework includes feature files that look like plain text as NL. Also, it gives clarity of QA or expansion output. This tool gives detailed thinking and reasoning features. 

Lettuce

This is also a BDD testing framework under Python testing. Also, it makes the testing process easier, and more scalable. This facilitates building different test scenarios. Further, there are steps included in this process. Such as:-

Behavior description

Running the code simply

Defining steps within Python

Changing the code to pass the test

Finally, running the changed code.

Following these steps helps to complete the process easily.

After following and repeating these steps three to four times makes the software free from errors and bugs. Also, it improves the software quality to great extent.

Therefore, Python is useful for automation testing extensively. This is because it has rich library space for making tests simpler. It has more stateless functions and uses a simple syntax to build readable tests. Also, it bridges the gap between the test cases and test code easily. With a simple and rich toolset and good structure, it is useful for scaling up the growth process. 

Advantages of Python unit testing

The following are the most valuable benefits of python testing.:-

This testing solution helps users to detect errors and bugs early in the growth lifecycle.

Also, it helps to better programs and codes easily.

Moreover, it easily syncs or merges with other methods and tools.

Also, this testing framework is easier and simple to modify.

Most IT developers use and prefer this technology so that they can easily carry out software testing. 

Final Words

Thus, this is all about Python testing tools and frameworks that help very much in testing software. It helps to deliver good and reliable software on time. These testing tools support almost all platforms and OS. Moreover, Python is easy to code and use with open and free coding language with strong community support. 

The reason behind choosing python for testing software is that the quality and structure of the scripts fulfill the user’s purposes. Also, these testing scripts are easier and simple to develop. To learn more in this regard, get into the Python Online Training with ITGuru industry experts. This learning may help you enhance your existing software testing skills with expert guidance.