Top 5 Python Testing Frameworks for Test Automation

Python Testing Frameworks

Python was voted the best programming language of 2018 and continues to rise up the charts. According to the index published by Tiobe, Python is currently ranked third in programming languages after Java and C. The popularity of Python-based test automation frameworks is growing due to the increased use of the language. It is not surprising that developers and testers can get confused when choosing the right Python testing frameworks for their projects. You should consider many things when choosing the right framework.

These include the script quality, ease of use, and how the modules are run. Here’s my attempt to show you the five best Python testing frameworks for testing automation. I also list their strengths and weaknesses. This will allow you to choose the best Python framework for your test automation needs.

Top 5 Python Testing Frameworks for Test Automation

1. Robot Framework

Robot Framework is one of the most popular Python testing frameworks that can be used for both acceptance-test-driven development and acceptance testing. It is written in Python but can be used on IronPython (which is. net-based) and Java-based Jython. Robot as a Python framework is compatible with all platforms, Windows, MacOS, and Linux.


  • You can only use Robot Framework (RF) Only if you have Python 2.7.14 installed or any version higher. While Python 3.6.4 can also be used, the code snippets in the official blog will ensure that the correct notes are made, including all necessary changes.
  • You’ll also need to install the “pip”, or Python package manager.
  • A development framework is also a must-have. The PyCharm Community Edition is a popular framework for developers. You can use any IDE you’ve used before, as code snippets don’t depend on the IDE you are using.

Advantages and Disadvantages of Robots

Let’s look at Robot’s advantages and disadvantages over other Python frameworks.


  • It makes automation easier by allowing testers to easily create readable test cases using a keyword-driven test method.
  • It is easy to use test data syntax
  • It includes test libraries and generic tools, which allow you to use individual elements in different projects.
  • Because it uses many APIs, the framework is extensible.
  • Robot Framework allows you to run parallel tests using a Selenium Grid. However, this feature has not been built in.


  • Although the Robot framework is not easy to use when creating custom HTML reports, it can be very useful. You can still present xUnit-formatted short reports using the Robot framework.
  • The Robot framework also has a flaw: parallel testing is not sufficient.

Is Robot the Best Python Test Framework for you?

If your experience in programming is limited and you’re a beginner in automation, Robot is a better Python test framework than Pytest and Pyunit. because it uses rich libraries and an easier-to-use DSL for testing. If you are looking to build a complex automation system, It is better to switch over to Pytest or another framework that uses Python code

Also read: Top 20 Python Libraries

2. Pytest

Pytest is another of the best Python testing frameworks for automation and software testing that is used for all types of software testing. This is an open-source framework and easy to use. It can be used by QA and development teams as well as individual practice groups and open-source projects. Many projects, including those of great stature like Dropbox and Mozilla, have moved from the unit test (Pyunit) to Pytest because of its useful features like “assert writing”. Let’s dive deep and discover what makes this Python framework so unique.


Pytest doesn’t require any special knowledge beyond a basic understanding of Python. You only need a functioning desktop with:

  • Command line interface
  • Python package manager
  • IDE for development

Advantages and Disadvantages of Pytest


  • Before Pytest arrived, the Python testing community used large classes to house their tests. Pytest brought a revolution because it allowed developers to create test suites in much smaller formats than they did before.
  • Other testing tools require that the tester or developer use a debugger to check logs or detect where a particular value is coming from. Pytest allows you to create test cases that allow you to store all values and tell you what value was asserted and failed.
  • Because the boilerplate code isn’t needed, it makes tests easier to write and more understandable.
  • You can add an argument to your test function to fixtures, which are functions that you can use.
  • They are responsible for returning values. Pytest allows you to make them modular by using one fixture after another. Multiple fixtures allow you to cover all possible parameter combinations without having to rewrite test cases.
  • Pytest developers released some plugins to make the framework more extensible. pytestxdist is a plugin that allows parallel testing to be performed without the need for a separate test runner. Parameterization of unit tests is possible without having to duplicate any code.
  • Developers are provided with special routines that simplify test case writing and make it less likely to fail. Also, the code becomes easier to understand.


  • Pytest uses special routines, so you need to compromise on compatibility. While you can write test cases quickly, it won’t allow you to use them with any other testing framework.

Is Pytest the Best Python Test Framework?

You must first learn a language. Once you are comfortable with it, you can move on to other languages. You will have all the features such as static code analysis, multiple IDE support, and most importantly, efficient test cases. It is better than unittest for writing functional test cases and creating complex frameworks. However, if you are looking to create a simple framework, its advantage is similar to the Robot framework.

3. UnitTest (PyUnit).

Unittest (or PyUnit) is the standard unit testing automation framework that comes with Python. It is heavily inspired by JUnit. The base class TestCase provides all the cleanup and set-up routines, as well as the assertion methods. Each method in the TestCase subclass begins with “test” which allows them to be run as test cases. The load methods and TestSuite classes can be used to add tests to the group. You can combine them to create custom test runners. Like Selenium testing with JUnit, unitTest also has the ability to use unitTest-sml-reporting and generate XML reports.


Since unitTest is included by default with Python, there are no prerequisites. You will need to have a basic knowledge of Python and the if framework in order to use it. Pip is required to enable additional modules. You will need pip installed along with an IDE to develop.

Advantages and Disadvantages of PyUnit


  • Unittest is part of Python’s standard library. There are many benefits to using Unittest.
  • Developers don’t need to install additional modules since the box comes already installed.
  • Unittest is xUnit’s derivative. Its working principle is the same as other xUnit frameworks. It is easy to use for people who don’t have a strong Python background.
  • It is possible to run individual test cases more easily. You only need to specify the names of the test cases on the terminal. It is also concise, which makes it easy to execute test cases.
  • The test reports are generated in milliseconds.


  • Normally, snake_case will be used to name Python codes. This framework was a lot inspired by Junit. However, the traditional camelCase name method still applies. This can make things confusing.
  • Sometimes the intent of the test codes can become unclear because it supports abstraction too much.
  • It is necessary to have a lot of boilerplate code.

Is PyUnit the Best Python Test Framework for You?

According to my opinion and that of other Python developers, Pytest introduced some idioms which allowed testers to write more automated code in a compact way. Unittest is a default Python test automation framework. However, its working principles and naming conventions differ from standard Python codes, and the requirement for too much boilerplate code makes it not a preferred framework.

4. Behave

Behaviour driven development is the latest agile-based software engineering methodology. It encourages developers, business people, and quality analysts, to work together. Behave, another top Python testing framework, allows teams to perform BDD testing without any difficulties. This framework’s nature is very similar to SpecFlow or Cucumber for automated testing. The test cases are written in plain English and then reattached to the code for execution. The behavior specifications define the behavior and then the steps can be reused in other scenarios.


Anyone should have basic Python knowledge to be able to use Behave. Let’s look at the prerequisites.

  • Behave requires that you install Python above 2.7.14 before installing it.
  • Behave requires a Python package manager (or pip).
  • The development environment is the most essential thing you will need. Pycharm is the preferred IDE by most developers.

Advantages and Disadvantages of Behave

As with all behavior in driven testing frameworks, opinions regarding Behave’s benefit vary from one person to the next. Let’s look at some of the most common pros and cons of using Behave.


  • Semi-formal language is used to express system behavior. A domain vocabulary keeps it consistent within the organization.
  • Teams of developers working on modules with similar features must be properly coordinated.
  • All types of test cases can be executed using building blocks.
  • Details are a result of reasoning and thinking.
  • Managers and stakeholders have a better understanding of the output of devs and QAs due to the similar format of the specifications.


  • It is only suitable for black box testing.

Is Behave the Best Python Test Framework for You?

As we mentioned, Behave (the Python framework) is best used for black box testing. Web testing is an excellent example because use cases can be explained in plain English. Behave is not recommended for integration testing and unit testing. The verbosity of Behave will only create complications in complex test scenarios. Both developers and testers recommend Python-bdd. This alternative to Behave is pytest-bdd. It implements all the good stuff in Pytest for testing behavior-driven scenarios.

Also read: Cloud Based Software Testing: What is it and it’s Advantages & Disadvantages

5. Lettuce

Lettuce is another easy-to-use behavior-driven automation tool that is based on Python and Cucumber, which can be found here. Lettuce’s main goal is to simplify and entertain behavior-driven development by focusing on the most common tasks.


You will need, at minimum Python 2.7.14, and an IDE is required. You can choose to use Pycharm, or any other IDE you prefer. You will also need to install the Python package manager in order to run tests.

Advantages and Disadvantages of Lettuce


  • Lettuce allows developers to create multiple scenarios and then describe the features using a simple, natural language.
  • Because the specifications are similar, it is important that both Dev and QA teams work together.
  • Lettuce can be used to run behavior-driven tests in black box testing.


  • Lettuce is a Python framework that has one drawback. Communication is essential for the successful execution of behavior-driven tests. This communication must be between developers,
  • QA and stakeholders. Communication gaps or absence of communication will cause the process to be unclear and teams can raise questions.

Is Lettuce the Best Python Test Framework for You?

Cucumber is more effective in executing BDD testing, according to automation testers and developers. But, if you are talking about Python developers or QA, pytest_bdd is the best replacement. This framework combines all the great features of Pytest such as compactness and easy-to-understand code with the verbosity that behavior-driven testing offers.

Wrapping up

The article below discusses the five best Python testing frameworks for test automation. They are based on different testing methods. While Pytest and Robot frameworks are great for unit and functional testing, Lettuce and Behave can be used for behavior-driven testing.

We can conclude that Pytest is the best for functional testing based on the above features. The Robot framework is an excellent tool for learning Python-based automation testing. Although it has a few limitations, the Robot framework will allow you to quickly get started. Lettuce or Behave can be used for Python-based BDD testing. However, if you have some experience with Pytest, pytest_ is better.

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