Automation is an essential element of the current software development process that creates an opportunity to expand the activities of teams and, at the same time, minimize the chance of errors. Companies are still resorting to automation, with more organizations committing to accelerate the rate of digital transformation in the development process, enhance the quality of software, and the automation of time-consuming practices. Python frameworks offer the basis of scalable, maintainable, and robust automation testing.
The current IT industry is dominated by automation, which includes cloud computing, cybersecurity, big data processing, and software testing. Python frameworks are essential in undertaking tasks since they simplify them compared to the past, given that they are convenient when dealing with the automation of complex processes. Python can be applied to every sphere and is applied to artificial intelligence, e-commerce, healthcare, finance, and many others.
These frameworks can be easily used by both inexperienced and skilled professionals to automate, minimize the involvement of a human factor, and increase the overall efficiency. It can be, thus, concluded that Python frameworks are among the most significant elements of success in the digital economy as they allow organizations to do away with errors in large-scale operations. In this blog, we will discuss the best Python frameworks that are defining the future of automated testing.
Leading Frameworks for Automation in Python
Here are some of the most common and widely applied Python automation frameworks:
PyTest
PyTest is a fast and adaptive testing framework that allows functional and unit testing with a small setup. This is what makes it excellent to run automated tests since it is highly supported by the plugin, and it is naturally linked to the fixtures. PyTest is employed in non-opinionated testing with a short form of test letters and a syntax that is easy to comprehend.
With the use of the pytest-xdist plugin, it can run in parallel and speed up the execution of tests, making it highly helpful to run large test suites. The functionality of the framework can be enhanced at any time in any of the areas due to the vast number of available plugins.
Robot Framework
Robot Framework is a keyword-driven, tabular testing, review, and acceptance check-based RPA test automation tool. It is not complicated in its syntax, and it can be rather flexible to be used with other tools like Appium and Selenium.
Read this guide on what is Selenium WebDriver to know more.
One of the greatest characteristics of Robot Framework is that it has its own language, which is easy to comprehend and can be written by both technical and nontechnical individuals. It does not depend on many third-party add-ons because it has built-in libraries characterized by the testing of the web database and APIs. Behavior-driven development (BD, D) is one of its features, which helps the teams to describe test cases in a structured and well-formatted way.
Behave
Behave is a tool of BDD that assists teams in specifying tests in the Gherkin language. It improves the work of the stakeholders, testers, and developers effectively and efficiently. The same is one of the specific behavior-driven development tools that assist testers and developers in the automation of test processes, since the tests may be written in the Gherkin language.
Thus, in a sense of an overall picture, test cases are nearer to the business requirements and more multidimensional for developers, testers, and business sides. It can be used in API testing and can also be applied along with Selenium, and is also suited for end-to-end testing of any program.
Lettuce
Lettuce is a lightweight and easy-to-use behavior-driven development (BDD) framework that adds simplicity and clarity to the process of writing test scenarios. Lettuce is an inspired-by-Cucumber library written in Python that enables testers and developers to express application behavior in plain English using the Gherkin syntax. This will facilitate the involvement of the non-technical stakeholders, such as product owners or business analysts, in the testing process.
Lettuce is suitable for small to medium projects where readability and simplicity of tests are more important than deep customization. It can be combined easily with Selenium to automate browsers and can be used to do end-to-end testing of web applications. Although there are fewer features and plug-ins when compared to more evolved BDD frameworks such as Behave, Lettuce is a good option for those who want to implement BDD practices in an easy and simple manner.
unittest (PyUnit)
unittest, which is also referred to as PyUnit, is the standard testing framework shipped with the standard library of Python. It is based on the xUnit architecture style employed by such frameworks as JUnit (Java) and NUnit (NET), and is therefore a familiar option to developers familiar with other programming languages. unittest is specially suited to the writing of organized and maintainable unit tests.
It supports test discovery, test suites, and setup and teardown procedures, and a wide variety of assertion methods. It may not be as feature-complete or concise as other frameworks, like Pytest, but it is a stable choice, and has long-term support in the Python ecosystem, so it is a safe choice, especially on legacy systems or teams with very highly-regulated environments. It is already incorporated in Python; thus, there is no need to install it separately. It is thus an opportune place to begin with the automation of a basic team with the desire to automate as fast as possible.
Nose2
Nose2 is an official replacement of the original Nose testing framework, which aims at expanding the functionality of Python’s built-in unittest module in a backward-compatible manner. It offers a plug-in-based architecture that improves test discovery, execution, and reporting. Nose2 allows you to write tests in unittest style, but adds access to other features, including test generators, code coverage interoperability, and parallel test execution via plugins.
This provides an effective alternative to unittest for teams who want the framework of unittest but require greater flexibility and extensibility for large projects. It is also possible to easily scale test suites as your application scales, since nose2 supports automatic test discovery. Even though it lacks the user base of Pytest, it can still be a useful framework to developers who want to modernize legacy Nose test suites or move toward more advanced unittest setups in phases.
See also: See the Full Picture: How Operational Assessment Drives Better Performance
Streamline Your Regression Testing Workflow with LambdaTest
Regression testing is necessary to ensure that new code does not cause any of the existing functionality to fail, but it is a highly time-consuming, error-prone activity that needs the right infrastructure. LambdaTest puts an end to the pain of regression testing with its fully scalable, cloud-based testing infrastructure that you can leverage to run your test suites on 3,000+ real browsers, devices, and OS combinations in a snap.
Whether it is unit tests, UI regression suites, or entire end-to-end pipelines, LambdaTest allows the most popular Python frameworks, including Pytest, unittest, and Robot Framework. It is fast to debug, has low manual work, and you can be sure of the cross-platform capabilities with parallel test execution, intelligent visual regression, and auto-generated screenshots.
Why LambdaTest for Regression Testing?
LambdaTest is not just any other cloud-based testing platform, but a powerful tool specifically designed to make regression testing simple and faster, regardless of the phase of the development lifecycle. These are the ways LambdaTest can bring true value to your regression testing:
Speed up Delivery through Parallel Testing: The test suite to run large regression tests may require hours to run, particularly when running them sequentially. Using the parallel testing feature in LambdaTest, you can run as many test cases per run as you want in various browser-device combinations and slash the total test time by a very large margin.
What this means is that you no longer need to make any tradeoffs in test coverage, nor need to delay deployments due to the need to wait a long time to run tests.
Test on 3000+ Real Browsers and Devices: The largest obstacle to regression testing is that you want your application to work the same way in the wide world of browsers, devices, and operating systems. LambdaTest fixes this by providing you with immediate access to a cloud-based lab of 3000+ real browser-OS-device combinations, thus enabling you to test where your users truly are. No matter whether you are working on the latest version of Chrome on Windows, Safari on macOS, Firefox on Linux, or even older mobile devices with legacy browsers, LambdaTest makes sure that all of the devices are covered without the burden of maintaining physical infrastructure.
Integrate Seamlessly with CI/CD Pipelines
With the modern rapid development pace, continuous integration and continuous delivery (CI/CD) are the way to deliver reliable software fast. Regression testing should be closely integrated with your CI/CD pipeline so that it can identify bugs as soon as they appear and keep your application stable as code modifications trickle in. This is easy to do with LambdaTest because it has native integrations with all the popular CI/CD tools, such as Jenkins, GitHub Actions, GitLab CI, Bitbucket Pipelines, Azure DevOps, Bamboo, and CircleCI.
Conclusion
When you select an automation testing tool, it has little to do with popularity, but rather how well it matches the needs of your projects, the expertise of your teams, and your application. Each of the Python frameworks we’ve discussed has its special contribution to make: whether it’s the versatile and scalable testing ability of Pytest or the keyword-driven nature of Robot Framework, or the ease of use with which a beginner can learn BDD with Lettuce.
When you’re in a highly iterative agile environment, a framework such as Pytest or Behave can help you be quick on your feet and keep your test design clear. Teams that are using automation as part of their CI/CD pipelines need the flexibility to write maintainable, modular tests with good reporting capabilities, which tools such as Testify and Nose2 excel at. In the meantime, legacy systems or teams with little or no experience with testing may find unittest to be predictable and structured, and able to be extended in the future to more capable tools.
Finally, the correct framework will make your QA process more powerful, and less manual work will be required to detect bugs early, before they get to production. With the increasing need for quality software, the use of an appropriate Python framework in automation testing may be the solution to your software development lifecycle.
