Python Automation Testing: Benefits and Importance

This blog article explains Python's importance for automated software testing and compares Python testing frameworks.

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Humans and computers share many talents. We are both thinking beings in the sense that we primarily take in and process information. We are both language-oriented beings in that we frequently base our interactions with others on a shared set of symbols. The parallels end there, however, and surgically implanted microchips are becoming more prevalent.

Humans have several advantages over machines, including the ability to show empathy and use critical thinking skills in complex situations. Computers, on the other hand, are fantastic at performing repetitive, tedious activities that we humans either can't or wouldn't like to undertake because of our lack of consistency, precision, and speed.

Humans dislike completing repetitive tasks. We find them comforting and calming, at least to some degree. Yet, in most cases, we find them uninteresting and tiresome. People are motivated when they are given opportunities for personal and professional growth, such as when they are given challenging tasks that lead to tangible rewards. We generally want to avoid having to enter the same data into a spreadsheet many times.

One of the finest ways that people and computers can work together for mutual benefit is in this scenario. Programming languages like Python allow us to automate the execution of repetitive but necessary operations.

Let's look at how the Python programming language can be used to automate tasks.

What Is Python Automation Testing?

Before you can use Python for automation, you'll need to know two things: what automation is and what Python is. You might have a general idea of what these names mean, but it's always good to know them in more detail.

Automation is the process of turning a task that used to be done by hand into one that happens automatically.

To learn more about test automation, read the ultimate guide: What is Automation Testing? Types, Examples, Process.

To automate a task, a framework needs to be turned on. This structure, a piece of code for our purposes, allows the task to be completed automatically without any input from the user.

What makes someone decide to automate a task? Mainly there are two reasons.

  • Most of the time, when you automate a task, it can be done much faster.
  • Mistakes are less likely to happen when a task is automated because human error has less effect.

To learn why test automation is helpful, read our guide: Top 12 Benefits of Test Automation.

Python is an open-source programming language that is flexible and easy to learn and use because it is similar to the English language.

Python's syntax is more understandable and readable compared to other programming languages. Plus, since it's open source, many tools, libraries, frameworks, and different kinds of support exist. Because of this, Python is one of the best languages for running simple automation.

The simple syntax of Python is the most well-known reason software engineers use it so much. Python code is far more similar to the English language than code written in other languages. Also, Python code tends to be shorter and uses fewer lines to do the same things as other languages. This makes it easy for both new and old programmers to learn Python.

Python's easy-to-use design makes it easy for programmers of all levels to use, so it takes less time and effort to start writing helpful Python scripts. Python scripts can automate many tedious, time-consuming, and energy-draining tasks.

But why are Python scripts so good for automating tasks? The answer is straightforward. Python has excellent support for data structures. You can store and get to data with the help of data structures. Data structures come in many forms, like a list, a set, or even a dictionary. You can even make your own data structures with Python. With this kind of flexibility, you can automate almost anything you can think of.

Python Testing Frameworks for Automation Testing

Here we listed Python testing frameworks for automation testing. You can also check out our comprehensive guide to Test Automation Framework: Benefits, Types & How to Choose.

Robot Framework

It is a free and open-source test automation platform that facilitates acceptance testing, acceptance test-driven development (ATDD), and robotic process automation (RPA). This framework is based on the Keyword Driven Testing method, making it easy for testers to create test cases without knowing how to code. It works with all OS and app types (web, mobile, and desktop).

Read Also: 5 Failures in Test Automation: Best Practices for Dealing with Them.


It is a free and open-source tool for automating tests across several web-based platforms, including unit and functional tests and API testing. Pytest can be used for functional test cases that are both simple and complicated. 

It works with the Test-Driven Development method and lets you run tests in parallel with the pytest-xdist plugin. Several Python testing frameworks are compatible with Pytest, including Unittest and Pyunit.

Check out our list of the Top 20 Automation Testing Tools.

Unittest or PyUnit

As a component of Python's standard library, it serves as the language's default testing framework. Unittest is based on the xUnit framework and is similar in some ways. 

UnitTest Framework is one of the most popular Python Unit testing frameworks due to its simple installation and Configuration options.

Read Also: Is Test Automation A Good Career Choice In 2023?


It's a free, all-inclusive framework for automating tests. This test framework makes it easy for testers to create test cases for mobile, web, or general automation. 

It's a framework that lets you create and run automated tests for the web, mobile, and generic platforms with a single executable agent and the necessary third-party libraries. 

It automatically sends out free PDF and HTML reports.

Read Also: Test Automation Strategy: Importance, Benefits & Example


It is a unit testing framework built on Python that can be used to run DocTests and UnitTests. Nose2 is a Domain-Specific Language (DSL) for writing functional tests. 

It comes with an ecosystem of plugins that make testing easy and quick.


It is one of the most popular Python frameworks for testing software development based on how things work. 

This framework lets testers write test cases in a language that is easy to understand and comes with good documentation.


Testify is a new way to do what Unittest and Nose used to do. 

Unittest doesn't have as many features as it does. This framework can test units, systems, and how they work together.


It is a Cucumber-based Python framework for behavior-driven development. It can communicate in the Gherkin language. 

Even testers who don't know much about technology can use this language to make automated tests.


The Pros of Automation Using Python

Here are some more pros of Python.

  • The Zen of Python, a set of rules for writing in Python, is an excellent guide for automating tests. It reminds you of the simple rules that make test scripts work well. Tests should be easy to understand, read, clear, relevant, and challenging but not too hard. Some might say these things are apparent, but The Zen of Python is a manifesto that won't let you forget the basics.
  • Pytest is one of the best frameworks for automating tasks that you can use. It can handle any functional test, including unit testing, integration testing, and end-to-end testing. Test cases are written as simple functions that can accept inputs based on parameters.
  • Plugins add to pytest's features and let you cover code, run multiple tests at once, and connect it to other frameworks like Django and Flask.
  • Its extensive library of valuable packages and ready-to-use parts for automation makes Python testing much easier.
  • Python is based on objects and has functions. It lets you choose between functions and classes, depending on what works best for your tasks. Distributed operations don't have any side effects and are easy to read because they have simple syntax.
  • Command Line can control the whole process of automating tests. Every test framework can start a console that can be used to look for and run tests. Rich support for the command line makes test management much easier. Exploratory testing can also be done with Python automation. You can get an app to a point where it needs to be tested by hand with Python calls. Python is excellent for both new and experienced users because it is scalable.
  • Scalability can be achieved by using the right syntax, a good structure, modules, and a large set of tools. It is also possible to combine many tools and processes from the side.


Testim - Pyhton Test Automation 

Koombea - Python Automation 

Lambdatest - Pyhton Test Automation 

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