In this article, we'll list top 5 Python Frameworks for Test Automation in 2019.
After being voted as the best programming language in the year 2018, Python still continues rising up the charts and currently ranks as the 3rd best programming language just after Java and C, as per the index published by Tiobe. With the increasing use of this language, the popularity of test automation frameworks based on Python is increasing as well. Obviously, developers and testers will get a little bit confused when it comes to choosing the best framework for their project. While choosing one, you should judge a lot of things, the script quality of the framework, test case simplicity and the technique to run the modules and find out their weaknesses. This is my attempt to help you compare the top 5 Python frameworks for test automation in 2019, and their advantages over the other as well as disadvantages. So you could choose the ideal Python framework for test automation according to your needs.
Used mostly for development that is acceptance test-driven as well as for acceptance testing, Robot Framework is one of the top Python test frameworks. Although it is developed using Python, it can also run on IronPython, which is .net-based and on Java-based Jython. Robot as a Python framework is compatible across all platforms – Windows, MacOS or Linux.
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Let’s take a look at what are the advantages and disadvantages of Robot as a test automation framework over other Python frameworks.
If you are a beginner in the automation domain and have less experience in development, using Robot as a top Python test framework is easier to use than pytest or pyunit, since it has rich in built libraries and involves using an easier test-oriented DSL. However, if you want to develop a complex automation framework, it is better to switch to pytest or any other framework involving Python code.
If you are new to Robot framework, here is a document that would help you run your first automation script using Robot framework with Selenium.
Used for all kinds of software testing, pytest is another top Python test framework for test automation. Being open source and easy to learn, the tool can be used by QA teams, development teams as well as individual practice groups and in open source projects. Because of its useful features like ‘assert rewriting’, most projects on the internet, including big shots like Dropbox and Mozilla, have switched from unittest(Pyunit) to pytest. Let’s take a deep dive and find out what’s so special about this Python framework.
Apart from working knowledge in Python, pytest does not need anything complex. All you need is a working desktop that has a command line interface, python package manager and an IDE for development.
The fact that special routines are used by pytest means that you have to compromise with compatibility. You will be able to conveniently write test cases but you won’t be able to use those test cases with any other testing framework.
Well, you have to start by learning a full-fledged language but once you get the hang of it, you will get all the features like static code analysis, support for multiple IDE and most importantly, writing effective test cases. For writing functional test cases and developing a complex framework, it is better than unittest but its advantage is somewhat similar to Robot Framework if your aim is to develop a simple framework.
If you are considering Pytest as a top Python test framework for you then here is a guide to test automation using pytest and Selenium WebDriver.
Unittest or PyUnit is the standard test automation framework for unit testing that comes with Python. It’s highly inspired by JUnit. The assertion methods and all the cleanup and setup routines are provided by the base class TestCase. The name of each and every method in the subclass of TestCase starts with “test”. This allows them to run as test cases. You can use the load methods and the TestSuite class to the group and load the tests. Together, you can use them to build customized test runners. Just like Selenium testing with JUnit, unittest also has the ability to use unittest-sml-reporting and generate XML reports.
There are no such prerequisites since unittest comes by default with Python. To use it, you will need standard knowledge of the python framework and also if you want to install additional modules, you will need pip installed along with an IDE for development.
Being part of the standard library of Python, there are several advantages of using Unittest.
In this article, we'll look into testing Node.js apps. We'll use Mocha, Chai and SinonJS, and delve into using spies, stubs and mocks.
Why this guide can take your testing skills to the next level
A thorough introduction to the Mocha test framework by the maintainer of Mocha, and how to use it to test your Node.js applications. Testing Node.js with Mocha