Flaky tests have become a very common scenario when implementing test automation. It is such a scenario where tests inconsistently pass or fail without even implementing any changes to the primary code base of the application. To resolve this process, developers often resort to the integration of Selenium Python with their testing scenario.

Are you planning to implement a similar solution? This is the perfect blog for you. We will go through various practical techniques, plugins, and best practices to create stable and reliable tests in Selenium Python. During our discussion, we will also try to ensure that the continuous integration and continuous deployment pipelines remain smooth and trustworthy.

Understanding Flaky Tests in Selenium

Before we start discussing the possible solutions to tackle flaky tests in selenium, let us go through some of the major reasons that give rise to these instances:

• Flaky tests can arise due to timing issues when elements might not load immediately. This causes interactions with absent elements which can give rise to severe errors during the test rendering process.
• External dependencies can also cause flaky test cases. If you have tests depending on external systems like networks, databases and APIs, it will fail when these dependencies are unavailable or unstable.
• Finally, Flaky test cases can also arise due to race conditions. This is because when multiple test actions try to access or modify shared resources simultaneously, they can lead to inconsistencies in the final Test results.

To further improve our understanding of these scenarios, let us shift our attention towards some of the most common real-world scenarios:

• When your website has multiple dynamic loading elements, the test will fail because the web element was not yet available when Selenium tried to interact with it.
• This can also fail due to external API calls. The test will fail intermittently when a required API call times out or returns an error due to the instability in the primary network.
• Finally, you can also receive flaky tests when elements are visible under cerhttps://www.webinfoblog.com/good-website/tain conditions, like after user interactions but not available in other scenarios. This case will give rise to various inconsistent test reports.

Identifying Flaky Tests in PyTest

Now that we have understood the scenarios that can give rise to flaky tests, it is very important to understand the ways of identifying flaky tests using PyTest. It is quite relieving that PyTest comes natively with various features to achieve this goal:

• Firstly, you can rerun the tests with different configurations or environments to determine if they fail under specific conditions. This is a very important scenario to understand the impact of various variables on the functioning of your web elements.
• You can also use the “pytest-repeat” plugin which will allow you to run tests multiple times with a single run for identifying instability issues. It is also worth using the “pytest-flakefinder” plugin. This will help you to flag flaky tests by running them repeatedly and logging failures.

Strategies for Reducing Flakiness

We also suggest the developers to incorporate various efficient strategies for reducing flakiness in Selenium tests. Some of the most common strategies are mentioned below:

• You can use explicit waits to replace hard-coded “time.sleep()” statements. The major benefit of this approach is that it will allow the dynamic elements to finish loading before the system resumes the testing process.
• It is also useful to mock or stop external elements wherever possible. This approach will help you to avoid network dependent failures in case of unstable network bandwidth.
• You can also avoid using unstable element locators like “//div[2]/button” and instead use unique IDs or data attributes. To further improve our understanding regarding this tip, we have mentioned a sample code snippet for the same:

Instead of using:

time.sleep(5)

Use:

Parallel Testing to Enhance Efficiency

Modern test suites consist of thousands of individual test cases that are aimed towards verifying the functioning of all the elements present in an application. So, it becomes a very hectic and time consuming process to run all these tests individually and roll out the final application.

Running the tests in a parallel configuration can help reduce the overall test time.

But, the testers should also remember that parallel test execution requires careful handling of shared resources for avoiding conflicts.

The “pytest-xdist” plugin will allow you to run tests concurrently. We also recommend the testers to use this plugin for integrating Selenium Python with cloud-based platforms like LambdaTest.

LambdaTest is an AI-powered test orchestration and execution platform that lets you perform manual and automation testing at scale with over 3000 real devices, browsers, and OS combinations. This platform will also allow you to execute Selenium-based automation testing with Pytest.

To run the above testing scenario, you have to install selenium, PyTest, and the “pytest-xdist” plugin along with LambdaTest Selenium Grid integration. To perform this process, you simply have to enter the following code snippet in the terminal window:

pip install selenium pytest pytest-xdist

To further help you with the understanding, we also may have mentioned a sample test file that helps you execute the above process:

Using PyTest-Rerunfailures Plugin

You can use this plugin to rerun failed tests a specified number of times. The primary approach for implementing this step is to reduce severe failures that can be caused due to timing issues or network inconsistencies. To implement this step, you simply have to enter the following code in the terminal window:

pip install pytest-rerunfailures

However, the testers must remember that while rerunning tests can provide temporary stability. It is very important to identify the root cause that resulted in the failure. This approach will help you to prevent reliance on retries as a long-term solution for the application development and testing process.

Implementing Retry Mechanisms in Selenium Python

You can also implement retry mechanisms with decorators for retrying specific actions within the Selenium tests. For example, you can use Python’s built-in retry functionality, while retrying can be an effective way to handle transient issues.

To improve your understanding of this process, we have also attached the code snippet for this step:

The above example will retry clicking a button up to three times with a 2-second delay between each retry. While retries can be useful, we would suggest avoiding the overuse of this step. This is because it can hide underlying issues that can become a severe concern down the line for your end users.

Leveraging PyTest Fixtures for Improved Stability

We also suggest the testers to use PyTest fixtures to massively improve the stability of the test cases. This is because it will help you to standardize the test setup and the teardown process:

• It is important to organize test fixtures based on functionality like initializing drivers or setting up databases. This approach will help you to ensure a clean state before each test is initiated and executed.
• The testers can also use the “autouse=True” parameter with the test fixtures. This parameter will help create global fixtures that can run for every test file. You can take a look at the following code snippet to better understand the implementation of the above processes:

• Using fixtures for managing resources, such as browser sessions, will help reduce the likelihood of resource conflicts. This entire step is very important to ensure the stability of your Selenium automation test suites.

Integrating Test Stability Checks with CI/CD Pipelines

You should add test stability checks with your CI/CD pipelines to ensure that flaky tastes are identified and handled at the earlier stages of the development cycle. This approach will help you to maintain consistent code quality and also speed up the final application delivery process.

To further help you integrate test stability practices, we have mentioned some of the most relevant steps for this process:

• You can use tools like “pre-commit” to run selected test cases locally before they are committed to the code repository. This approach will help you to catch potential flaky behavior at the developer’s end during the early stages of the application development cycle. The attached code snippet will allow you to implement this step:

• You can also consider integrating the “pytest-rerunfailures” plugin with your continuous integration and continuous deployment scripts. This integration will automatically rerun the failed tests a specified number of times to ensure that severe issues do not immediately block the application delivery pipeline.

Best Practices for Writing Stable Selenium Tests in Python

Finally, let us divert our attention towards some of the best practices that will help improve your efficiency while aiming to write stable Selenium tests in Python:

• The first tip is to avoid hardcoded delays by replacing static waits with dynamic waits.
• We also suggest that developers to use assertions sparingly. You should only assert critical conditions and avoid complex syntax. This approach will help you to maintain the readability of the test, even for the non-technical members of the team.
• It is also important to ensure that all the test scripts are independent within the entire test suite. This is because tests should not rely on the state left by the previous test, as this can cause conflicts and failures. This practice will also help you to simplify rolling out future updates to the application infrastructure.
• You should also practice cleaning up after executing a testing scenario. By cleaning up resources, you can ensure that each test runs in isolation. Some of the important steps to achieve this goal include closing browser windows or cleaning cookies after the test execution process
• The final practice is to use proper element locators. We suggest the testers to use CSS selectors or IDs that are less prone to change.

All the above practices will massively contribute to a robust and reliable testing suite. It will also help minimize the impact of test flakiness over the entire infrastructure of the web application.

The Bottom Line

Based on all the factors that we analyzed in this article, we can safely conclude that creating a stable and reliable Selenium test suite in PyTest will require a strategic approach to managing flaky tests.

By implementing all the strategies discussed in this article and also using the appropriate plugins, you can reduce test flakiness and boost the efficiency of your test automation processes. It is also useful to integrate these practices into your workflows to ensure a more flexible continuous integration and continuous deployment pipeline.

As testers, we must remember that one of our main goals in automation testing is to reduce flaky tests and ensure that teams can focus on delivering high-quality code with confidence to maintain a positive brand reputation.