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Playwright Fixtures in Action : Create Reusable and Maintainable Tests

by Rajesh K | May 21, 2025 | Automation Testing, Blog, Latest Post | 8 comments

Setting up and tearing down test environments can be a repetitive and error-prone process in end-to-end testing. This is especially true when dealing with complex workflows or multiple test configurations. Enter Playwright Fixtures a built-in feature of Playwright Test that allows testers to define modular, reusable, and maintainable setup and teardown logic. Fixtures streamline your test code, eliminate redundancy, and ensure consistency across test runs. Whether you’re initializing browsers, setting up authentication states, or preparing test data, fixtures help you keep your test environment under control. In this blog, we’ll explore how Playwright Fixtures work, their built-in capabilities, how to create and override custom fixtures, automatic fixtures and fixture timeouts. You’ll leave with a comprehensive understanding of how to leverage fixtures to build robust and maintainable Playwright test suites.

What Are Playwright Fixtures?

Playwright Fixtures are reusable components in the @playwright/test framework used to define the setup and teardown logic of your test environment. Think of them as the building blocks that ensure your browser contexts, authentication sessions, and test data are ready to go before each test begins.

Fixtures help manage:

• Browser and context initialization
• Login sessions and cookies
• Data preparation and cleanup
• Consistent configuration across tests

By centralizing these operations, fixtures reduce boilerplate and boost code clarity. They prevent duplication of setup logic, reduce test flakiness, and make the tests more scalable and maintainable. To better illustrate the practical benefits of Playwright Fixtures, let’s dive into a realistic scenario that many testers frequently encounter validating the checkout flow in an e-commerce application.

Challenges in Repetitive Test Setup

Repeatedly preparing test conditions such as initializing browser contexts, logging in users, and setting up shopping carts for each test case can lead to redundant, bloated, and error-prone test scripts. This redundancy not only slows down the testing process but also increases maintenance efforts and potential for errors.

Streamlining Test Automation with Playwright Fixtures

Playwright Fixtures significantly improve this situation by allowing testers to define modular and reusable setup and teardown procedures. Let’s explore how you can use Playwright Fixtures to simplify and streamline your e-commerce checkout testing scenario.

Step 1: Define an Authenticated User Fixture

This fixture handles user authentication once, providing an authenticated browser session for subsequent tests.

import { test as base } from '@playwright/test';

const test = base.extend({
  authenticatedPage: async ({ browser }, use) => {
    const context = await browser.newContext();
    const page = await context.newPage();
    await page.goto('https://shop.example.com/login');
    await page.fill('#username', 'testuser');
    await page.fill('#password', 'password123');
    await page.click('#login');
    await page.waitForSelector('#user-profile'); // Confirm successful login
    await use(page);
    await context.close();
  },
});

Step 2: Define a Shopping Cart Setup Fixture

This fixture prepares a pre-filled shopping cart environment, eliminating repetitive product selection and cart preparation.

const testWithCart = test.extend({
  cartReadyPage: async ({ authenticatedPage }, use) => {
    await authenticatedPage.goto('https://shop.example.com/products/1');
    await authenticatedPage.click('#add-to-cart');
    await authenticatedPage.goto('https://shop.example.com/cart');
    await use(authenticatedPage);
  }
});

Step 3: Implementing the Checkout Test

Leverage the prepared fixtures to execute your checkout validation effectively.

testWithCart('Validate Checkout Flow', async ({ cartReadyPage }) => {
  await cartReadyPage.click('#checkout');
  await cartReadyPage.fill('#shipping-address', '123 Main St');
  await cartReadyPage.click('#confirm-order');
  await expect(cartReadyPage.locator('#confirmation-message'))
    .toHaveText('Thank you for your purchase!');
});

Using Playwright Fixtures, the previously cumbersome testing scenario now becomes straightforward and highly efficient:

• Reduced Redundancy: Setup logic defined clearly once, reused effortlessly.
• Enhanced Reliability: Consistent setup reduces flaky tests and ensures stability across test runs.
• Accelerated Execution: Dramatically reduced execution time, beneficial for continuous integration and delivery pipelines.
• Improved Maintainability: Modular approach simplifies updates and enhances readability.

By incorporating Playwright Fixtures in scenarios like this, testers and developers alike can achieve more reliable, maintainable, and scalable test suites, significantly boosting the quality and efficiency of software testing practices.

Built-in Fixtures in Playwright

Playwright provides several built-in fixtures when using the @playwright/test package. These are automatically available in your test function parameters:

Fixture – Description

• page – A single browser tab; most commonly used for UI interaction
• browser – A browser instance (Chromium, Firefox, or WebKit)
• context – An isolated browser context for separate sessions
• request – API RequestContext for making HTTP requests without a browser
• browserName – A string representing the current browser being tested
• baseURL – The base URL used in page.goto() or request.get()

Playwright comes packed with a variety of built-in fixtures that simplify common testing tasks right out of the box. These fixtures help manage browser instances, contexts, pages, and even API requests, allowing testers to write cleaner, more maintainable tests without redundant setup logic. Below are some commonly used built-in fixtures show how they enhance the efficiency and reliability of test scripts.

BrowserName Fixture

Detects the current browser being used and adjusts logic accordingly, allowing for cross-browser support and conditional test behavior.

import { test, expect } from '@playwright/test';

test('Test for Built-in browserName fixture', async ({ page, browserName }) => {
  await page.goto('https://www.google.co.in/');
  if (browserName === 'firefox') {
    console.log('Running test in Firefox Browser');
  }
  await expect(page).toHaveTitle('Google');
});

Browser and page Fixtures

Launches a browser in non-headless mode and opens a new page to verify the title of a website. Useful for visual debugging and testing in full UI mode.

const base = require('@playwright/test');

const test = base.test.extend({
  browser: async ({}, use) => {
    const browser = await base.chromium.launch({ headless: false });
    await use(browser);
    await browser.close();
  },
});

test('Open Facebook and check title', async ({ browser }) => {
  const page = await browser.newPage();
  await page.goto('https://www.facebook.com/');
  const fbTitle = await page.title();
  console.log(fbTitle);
});

Context Fixture

Creates a new isolated browser context for each test to avoid shared cookies or storage, which ensures better test isolation and prevents data leakage.

const base = require('@playwright/test');

const test = base.test.extend({
  context: async ({ browser }, use) => {
    const context = await browser.newContext();
    await use(context);
    await context.close();
  },
});

test('Open Facebook in isolated context', async ({ context }) => {
  const page = await context.newPage();
  await page.goto('https://www.facebook.com/');
  await base.expect(page).toHaveTitle('Facebook - log in or sign up');
  await page.close();
});

Request Fixture

Makes direct HTTP requests using Playwright’s request context, useful for API testing without launching a browser.

const { test, expect } = require('@playwright/test');

test('Make a GET request to ReqRes API', async ({ request }) => {
  const response = await request.get('https://reqres.in/api/users/2');
  expect(response.ok()).toBeTruthy();
  const body = await response.json();

  console.log(body);
  expect(body.data).toHaveProperty('id', 2);
});

Creating Custom Fixtures

Custom fixtures are created using test.extend(). These are useful when:

• You need reusable data (e.g., user credentials).
• You want to inject logic like pre-login.
• You want test-specific environment setup.

Custom testUser Fixture

Injects reusable test data like user credentials into the test. This promotes reusability and clean code.

import { test as base } from '@playwright/test';

const test = base.extend({
  testUser: async ({}, use) => {
    const user = {
      email: '[email protected]',
      password: 'securepassword123'
    };
    await use(user);
  }
});

test('Facebook login test using custom fixture', async ({ page, testUser }) => {
  await page.goto('https://www.facebook.com/');
  await page.fill("input[name='email']", testUser.email);
  await page.fill("input[id='pass']", testUser.password);
  await page.click("button[name='login']");
});

Custom Fixture Naming and Titles

Assigns a descriptive title to the fixture for better traceability in test reports.

import { test as base } from '@playwright/test';

export const test = base.extend({
  innerFixture: [
    async ({}, use, testInfo) => {
      await use();
    },
    { title: 'my fixture' }
  ]
});

Overriding Fixtures

Overrides the default behavior of the page fixture to automatically navigate to a base URL before each test.

const test = base.extend({
  page: async ({ baseURL, page }, use) => {
    await page.goto(baseURL);
    await use(page);
  }
});

test.use({ baseURL: 'https://www.demo.com' });

Automatic Fixtures

Runs shared setup and teardown logic for all tests automatically, such as authentication or data seeding.

const base = require('@playwright/test');

const test = base.test.extend({
  authStateLogger: [
    async ({}, use) => {
      console.log('[Fixture] Logging in...');
      await new Promise(res => setTimeout(res, 1000));
      await use();
      console.log('[Fixture] Logging out...');
    },
    { auto: true }
  ]
});

Fixture Timeouts

Ensures that long-running fixtures do not cause the test suite to hang by defining maximum allowable time.

const base = require('@playwright/test');

const test = base.test.extend({
  authStateLogger: [
    async ({}, use) => {
      console.log('[Fixture] Logging in...');
      await new Promise(res => setTimeout(res, 3000));
      await use();
      console.log('[Fixture] Logging out...');
    },
    { auto: true, timeout: 5000 }
  ]
});

Benefits of Using Playwright Fixtures

Benefit – Description

• Modularity – Reuse logic across test files and suites
• Maintainability – Centralized configuration means easier updates
• Test Isolation – Prevents cross-test interference
• Scalability – Clean, extensible structure for large suites
• Performance – Reduces redundant setup

Conclusion

Playwright Fixtures are more than just setup helpers they’re the backbone of a scalable, clean, and maintainable test architecture. By modularizing your environment configuration, they reduce flakiness, improve performance, and keep your tests DRY (Don’t Repeat Yourself). Start simple, think modular, and scale with confidence. Mastering fixtures today will pay dividends in your team’s productivity and test reliability.

Frequently Asked Questions

Playwright Visual Testing: A Comprehensive Guide to UI Regression

by Rajesh K | May 8, 2025 | Automation Testing, Blog, Latest Post | 6 comments

Playwright Visual Testing is an automated approach to verify that your web application’s UI looks correct and remains consistent after code changes. In modern web development, how your app looks is just as crucial as how it works. Visual bugs like broken layouts, overlapping elements, or wrong colors can slip through functional tests. This is where Playwright’s visual regression testing capabilities come into play. By using screenshot comparisons, Playwright helps catch unintended UI changes early in development, ensuring a pixel perfect user experience across different browsers and devices. In this comprehensive guide, we’ll explain what Playwright visual testing is, why it’s important, and how to implement it. You’ll see examples of capturing screenshots and comparing them against baselines, learn about setting up visual tests in CI/CD pipelines, using thresholds to ignore minor differences, performing cross-browser visual checks, and discover tools that enhance Playwright’s visual testing. Let’s dive in!

What is Playwright Visual Testing?

Playwright is an open-source end-to-end testing framework by Microsoft that supports multiple languages (JavaScript/TypeScript, Python, C#, Java) and all modern browsers. Playwright Visual Testing refers to using Playwright’s features to perform visual regression testing automatically detecting changes in the appearance of your web application. In simpler terms, it means taking screenshots of web pages or elements and comparing them to previously stored baseline images (expected appearance). If the new screenshot differs from the baseline beyond an acceptable threshold, the test fails, flagging a visual discrepancy.

Visual testing focuses on the user interface aspect of quality. Unlike functional testing which asks “does it work correctly?”, visual testing asks “does it look correct?”. This approach helps catch:

• Layout shifts or broken alignment of elements
• CSS styling issues (colors, fonts, sizes)
• Missing or overlapping components
• Responsive design problems on different screen sizes

By incorporating visual checks into your test suite, you ensure that code changes (or even browser updates) haven’t unintentionally altered the UI. Playwright provides built-in commands for capturing and comparing screenshots, making visual testing straightforward without needing third-party addons. Next, we’ll explore why this form of testing is crucial for modern web apps.

Why Visual Testing Matters

Visual bugs can significantly impact user experience, yet they are easy to overlook if you’re only doing manual checks or writing traditional functional tests. Here are some key benefits and reasons why integrating visual regression testing with Playwright is important:

• Catch visual regressions early: Automated visual tests help you detect unintended design changes as soon as they happen. For example, if a CSS change accidentally shifts a button out of view, a visual test will catch it immediately before it reaches production.
• Ensure consistency across devices/browsers: Your web app should look and feel consistent on Chrome, Firefox, Safari, and across desktop and mobile. Playwright visual tests can run on all supported browsers and even emulate devices, validating that layouts and styles remain consistent everywhere.
• Save time and reduce human error: Manually checking every page after each release is tedious and error-prone. Automated visual testing is fast and repeatable – it can evaluate pages in seconds, flagging differences that a human eye might miss (especially subtle spacing or color changes). This speeds up release cycles.
• Increase confidence in refactoring: When developers refactor frontend code or update dependencies, there’s a risk of breaking the UI. Visual tests give a safety net – if something looks off, the tests will fail. This boosts confidence to make changes, knowing that visual regressions will be caught.
• Historical UI snapshots: Over time, you build a gallery of baseline images. These serve as a visual history of your application’s UI. They can provide insights into how design changes evolved and help decide if certain UI changes were beneficial or not.
• Complement functional testing: Visual testing fills the gap that unit or integration tests don’t cover. It ensures the application not only functions correctly but also appears correct. This holistic approach to testing improves overall quality.

In summary, Playwright Visual Testing matters because it guards the user experience. It empowers teams to deliver polished, consistent UIs with confidence, even as the codebase and styles change frequently.

How Visual Testing Works in Playwright

Now that we understand the what and why, let’s see how Playwright visual testing actually works. The process can be broken down into a few fundamental steps: capturing screenshots, creating baselines, comparing images, and handling results. Playwright’s test runner has snapshot testing built-in, so you can get started with minimal setup. Below, we’ll walk through each step with examples.

1. Capturing Screenshots in Tests

The first step is to capture a screenshot of your web page (or a specific element) during a test. Playwright makes this easy with its page.screenshot() method and assertions like expect(page).toHaveScreenshot(). You can take screenshots at key points for example, after the page loads or after performing some actions that change the UI.

In a Playwright test, capturing and verifying a screenshot can be done in one line using the toHaveScreenshot assertion. Here’s a simple example:

// example.spec.js
const { test, expect } = require('@playwright/test');

test('homepage visual comparison', async ({ page }) => {
  await page.goto('https://example.com');
  await expect(page).toHaveScreenshot();  // captures and compares screenshot
});

In this test, Playwright will navigate to the page and then take a screenshot of the viewport. On the first run, since no baseline exists yet, this command will save the screenshot as a baseline image (more on baselines in a moment). In subsequent runs, it will take a new screenshot and automatically compare it against the saved baseline.

How it works: The expect(page).toHaveScreenshot() assertion is part of Playwright’s test library. Under the hood, it captures the image and then looks for a matching reference image. By default, the baseline image is stored in a folder (next to your test file) with a generated name based on the test title. You can also specify a name or path for the screenshot if needed. Playwright can capture the full page or just the visible viewport; by default it captures the viewport, but you can pass options to toHaveScreenshot or page.screenshot() (like { fullPage: true }) if you want a full-page image.

2. Creating Baseline Images (First Run)

A baseline image (also called a golden image) is the expected appearance of your application’s UI. The first time you run a visual test, you need to establish these baselines. In Playwright, the initial run of toHaveScreenshot (or toMatchSnapshot for images) will either automatically save a baseline or throw an error indicating no baseline exists, depending on how you run the test.

Typically, you’ll run Playwright tests with a special flag to update snapshots on the first run. For example:

npx playwright test --update-snapshots

Running with –update-snapshots tells Playwright to treat the current screenshots as the correct baseline. It will save the screenshot files (e.g. homepage.png) in a snapshots folder (for example, tests/example.spec.js-snapshots/ if your test file is example.spec.js). These baseline images should be checked into version control so that your team and CI system all use the same references.

After creating the baselines, future test runs (without the update flag) will compare new screenshots against these saved images. It’s a good practice to review the baseline images to ensure they truly represent the intended design of your application.

3. Pixel-by-Pixel Comparison of Screenshots

Once baselines are in place, Playwright’s test runner will automatically compare new screenshots to the baseline images each time the test runs. This is done pixel-by-pixel to catch any differences. If the new screenshot exactly matches the baseline, the visual test passes. If there are any pixel differences beyond the allowed threshold, the test fails, indicating a visual regression.

Under the hood, Playwright uses an image comparison algorithm (powered by the Pixelmatch library) to detect differences between images. Pixelmatch will compare the two images and identify any pixels that changed (e.g., due to layout shift, color change, etc.). It can also produce a diff image that highlights changed pixels in a contrasting color (often bright red or magenta), making it easy for developers to spot what’s different.

What happens on a difference? If a visual mismatch is found, Playwright will mark the test as failed. The test output will typically indicate how many pixels differed or the percentage difference. It will also save the current actual screenshot and a diff image alongside the baseline. For example, you might see files like homepage.png (baseline), homepage-actual.png (new screenshot), and homepage-diff.png (the visual difference overlay). By inspecting these images, you can pinpoint the UI changes. This immediate visual feedback is extremely helpful for debugging—just open the images to see what changed.

4. Setting Thresholds for Acceptable Differences

Sometimes, tiny pixel differences can occur that are not true bugs. For instance, anti-aliasing differences between operating systems, minor font rendering changes, or a 1-pixel shift might not be worth failing the test. Playwright allows you to define thresholds or tolerances for image comparisons to avoid false positives.

You can configure a threshold as an option to the toHaveScreenshot assertion (or in your Playwright config). For example, you might allow a small percentage of pixels to differ:

await expect(page).toHaveScreenshot({ maxDiffPixelRatio: 0.001 });

The above would pass the test even if up to 0.1% of pixels differ. Alternatively, you can set an absolute pixel count tolerance with maxDiffPixels, or a color difference threshold with threshold (a value between 0 and 1 where 0 is exact match and 1 is any difference allowed). For instance:

await expect(page).toHaveScreenshot({ maxDiffPixels: 100 });  // ignore up to 100 pixels

These settings let you fine-tune the sensitivity of visual tests. It’s important to strike a balance: you want to catch real regressions, but not fail the build over insignificant rendering variations. Often, teams start with a small tolerance to account for environment differences. You can define these thresholds globally in the Playwright configuration so they apply to all tests for consistency.

5. Automation in CI/CD Pipelines

One of the strengths of using Playwright for visual testing is that it integrates smoothly into continuous integration (CI) workflows. You can run your Playwright visual tests on your CI server (Jenkins, GitHub Actions, GitLab CI, etc.) as part of every build or deployment. This way, any visual regression will automatically fail the pipeline, preventing unintentional UI changes from going live.

In a CI setup, you’ll typically do the following:

• Check in baseline images: Ensure the baseline snapshot folder is part of your repository, so the CI environment has the expected images to compare against.
• Run tests on a consistent environment: To avoid false differences, run the browser in a consistent environment (same resolution, headless mode, same browser version). Playwright’s deterministic execution helps with this.
• Update baselines intentionally: When a deliberate UI change is made (for example, a redesign of a component), the visual test will fail because the new screenshot doesn’t match the old baseline. At that point, a team member can review the changes, and if they are expected, re-run the tests with –update-snapshots to update the baseline images to the new look. This update can be part of the same commit or a controlled process.
• Review diffs in pull requests: Visual changes will show up as diffs (image files) in code review. This provides an opportunity for designers or developers to verify that changes are intentional and acceptable.

By automating visual tests in CI/CD, teams get immediate feedback on UI changes. It enforces an additional quality gate: code isn’t merged unless the application looks right. This dramatically reduces the chances of deploying a UI bug to production. It also saves manual QA effort on visual checking.

6. Cross-Browser and Responsive Visual Testing

Web applications need to look correct on various browsers and devices. A big advantage of Playwright is its built-in support for testing in Chromium (Chrome/Edge), WebKit (Safari), and Firefox, as well as the ability to simulate mobile devices. You should leverage this to do visual regression testing across different environments.

With Playwright, you can specify multiple projects or launch contexts in different browser engines. For example, you can run the same visual test in Chrome and Firefox. Each will produce its own set of baseline images (you may namespace them by browser or use Playwright’s project name to separate snapshots). This ensures that a change that affects only a specific browser’s rendering (say a CSS that behaves differently in Firefox) will be caught.

Similarly, you can test responsive layouts by setting the viewport size or emulating a device. For instance, you might have one test run for desktop dimensions and another for a mobile viewport. Playwright can mimic devices like an iPhone or Pixel phone using device descriptors. The screenshots from those runs will validate the mobile UI against mobile baselines.

Tip: When doing cross-browser visual testing, be mindful that different browsers might have slight default rendering differences (like font smoothing). You might need to use slightly higher thresholds or per-browser baseline images. In many cases, if your UI is well-standardized, the snapshots will match closely. Ensuring consistent CSS resets and using web-safe fonts can help minimize differences across browsers.

7. Debugging and Results Reporting

When a visual test fails, Playwright provides useful output to debug the issue. In the terminal, the test failure message will indicate that the screenshot comparison did not match the expected snapshot. It often mentions how many pixels differed or the percentage difference. More importantly, Playwright saves the images for inspection. By default you’ll get:

• The baseline image (what the UI was expected to look like)
• The actual image from the test run (how the UI looks now)
• A diff image highlighting the differences

You can open these images side-by-side to immediately spot the regression. Additionally, if you use the Playwright HTML reporter or an integrated report in CI, you might see the images directly in the report for convenience.

Because visual differences are easier to understand visually than through logs, debugging usually just means reviewing the images. Once you identify the cause (e.g. a missing CSS file, or an element that moved), you can fix the issue (or approve the change if it was intentional). Then update the baseline if needed and re-run tests.

Playwright’s logs will also show the test step where the screenshot was taken, which can help correlate which part of your application or which recent commit introduced the change.

Tools and Integrations for Visual Testing

While Playwright has robust built-in visual comparison capabilities, there are additional tools and integrations that can enhance your visual testing workflow:

• Percy – Visual review platform: Percy (now part of BrowserStack) is a popular cloud service for visual testing. You can integrate Percy with Playwright by capturing snapshots in your tests and sending them to Percy’s service. Percy provides a web dashboard where team members can review visual diffs side-by-side, comment on them, and approve or reject changes. It also handles cross-browser rendering in the cloud. This is useful for teams that want a collaborative approval process for UI changes beyond the command-line output. (Playwright + Percy can be achieved via Percy’s SDK or CLI tools that work with any web automation).

• Applitools Eyes – AI-powered visual testing: Applitools is another platform that specializes in visual regression testing and uses AI to detect differences in a smarter way (ignoring certain dynamic content, handling anti-aliasing, etc.). Applitools has an SDK that can be used with Playwright. In your tests, you would open Applitools Eyes, take snapshots, and Eyes will upload those screenshots to its Ultrafast Grid for comparison across multiple browsers and screen sizes. The results are viewed on Applitools dashboard, with differences highlighted. This tool is known for features like intelligent region ignoring and visual AI assertions.

• Pixelmatch – Image comparison library: Pixelmatch is the open-source library that Playwright uses under the hood for comparing images. If you want to perform custom image comparisons or generate diff images yourself, you could use Pixelmatch in a Node script. However, in most cases you won’t need to interact with it directly since Playwright’s expect assertions already leverage it.
• jest-image-snapshot – Jest integration: Before Playwright had built-in screenshot assertions, a common approach was to use Jest with the jest-image-snapshot library. This library also uses Pixelmatch and provides a nice API to compare images in tests. If you are using Playwright through Jest (instead of Playwright’s own test runner), you can use expect(image).toMatchImageSnapshot(). However, if you use @playwright/test, it has its own toMatchSnapshot method for images. Essentially, Playwright’s own solution was inspired by jest-image-snapshot.
• CI Integrations – GitHub Actions and others: There are community actions and templates to run Playwright visual tests on CI and upload artifacts (like diff images) for easier viewing. For instance, you could configure your CI to comment on a pull request with a link to the diff images when a visual test fails. Some cloud providers (like BrowserStack, LambdaTest) also offer integrations to run Playwright tests on their infrastructure and manage baseline images.

Using these tools is optional but can streamline large-scale visual testing, especially for teams with many baseline images or the need for cross-team collaboration on UI changes. If you’re just starting out, Playwright’s built-in capabilities might be enough. As your project grows, you can consider adding a service like Percy or Applitools for a more managed approach.

Code Example: Visual Testing in Action

To solidify the concepts, let’s look at a slightly more involved code example using Playwright’s snapshot testing. In this example, we will navigate to a page, wait for an element, take a screenshot, and compare it to a baseline image:

// visual.spec.js
const { test, expect } = require('@playwright/test');

test('Playwright homepage visual test', async ({ page }) => {
  //  Navigate to the Playwright homepage
  await page.goto('https://playwright.dev/');

  // Wait for a stable element so the page finishes loading
  await page.waitForSelector('header >> text=Playwright');

  //  Capture and compare a full‑page screenshot
  //    • The first run (with --update-snapshots) saves playwright-home.png
  //    • Subsequent runs compare against that baseline
  await expect(page).toHaveScreenshot({
    name: 'playwright-home.png',
    fullPage: true
  });
});

Expected output

Conclusion:

Playwright visual testing is a powerful technique to ensure your web application’s UI remains consistent and bug-free through changes. By automating screenshot comparisons, you can catch CSS bugs, layout breaks, and visual inconsistencies that might slip past regular tests. We covered how Playwright captures screenshots and compares them to baselines, how you can integrate these tests into your development workflow and CI/CD, and even extend the capability with tools like Percy or Applitools for advanced use cases.

The best way to appreciate the benefits of visual regression testing is to try it out in your own project. Set up Playwright’s test runner, write a couple of visual tests for key pages or components, and run them whenever you make UI changes. You’ll quickly gain confidence that your application looks exactly as intended on every commit. Pixel-perfect interfaces and happy users are within reach!

Frequently Asked Questions

Tosca Jenkins Integration: Boost Your CI/CD Workflow Today

by Mollie Brown | Apr 21, 2025 | Automation Testing, Blog, Latest Post | 0 comments

Integrating Jenkins with Tricentis Tosca is a practical step for teams looking to bring more automation testing and consistency into their CI/CD pipelines. This setup allows you to execute Tosca test cases automatically from Jenkins, helping ensure smoother, more reliable test cycles with less manual intervention. In this blog, we’ll guide you through the process of setting up the Tosca Jenkins Integration using the Tricentis CI Plugin and ToscaCIClient. Whether you’re working with Remote Execution or Distributed Execution (DEX), the integration supports both, giving your team flexibility depending on your infrastructure. We’ll cover the prerequisites, key configuration steps, and some helpful tips to ensure a successful setup. If your team is already using Jenkins for builds and deployments, this integration can help extend automation to your testing layer, making automation testing a seamless part of your pipeline and keeping your workflow unified and efficient.

Necessary prerequisites for integration

To connect Jenkins with Tricentis Tosca successfully, organizations need to have certain tools and conditions ready. First, you must have the Jenkins plugin for Tricentis Tosca. This plugin helps link the automation features of both systems. Make sure the plugin works well with your version of Jenkins because updates might change how it performs.

Next, it is important to have a set up Tricentis test automation environment. This is necessary for running functional and regression tests correctly within the pipeline. Check that the Tosca Execution Client is installed and matches your CI requirements. For the best results, your Tosca Server should also be current and operational.

Finally, prepare your GitHub repository for configuration. This allows Jenkins to access the code, run test cases, and share results smoothly. With these steps completed, organizations can build effective workflows that improve testing results and development efforts.

Step-by-step guide to configuring Tosca in Jenkins

Achieving the integration requires systematic configuration of Tosca within Jenkins. Below is a simple guide:

Step 1: Install Jenkins Plugin – Tricentis Continuous Integration

1. Go to Jenkins Dashboard → Manage Jenkins → Manage Plugins.

2. Search for Tricentis Continuous Integration in the Available tab.

3. Install the plugin and restart Jenkins if prompted.

Step 2: Configure Jenkins Job with Tricentis Continuous Integration

Once you’ve installed the plugin, follow these steps to add it to your Jenkins job:

• Go to your Jenkins job or create a new Freestyle project.
• Click on Configure.
• Scroll to Build Steps section.
• Click Add build step → Select Tricentis Continuous Integration from the dropdown.

Configure the Plugin Parameters

Once the plugin is installed, configure the Build Step in your Jenkins job using the following fields:

Step 3: Create a Tosca Agent (Tosca Server)

Create an Agent (from Tosca Server)

You can open the DEX Monitor in one of the following ways:

• In your browser, by entering the address http://:/Monitor/.
  Directly from Tosca Commander.
• To do so, right-click a TestEvent and select one of the following context menu entries:
  Open Event View takes you to the TestEvents overview page.
  Open Agent View takes you to the Agents overview page.

Navigate the DEX Monitor

The menu bar on the left side of the screen allows you to switch between views:

• The Agent View, where you can monitor, recover, configure, and restart your Agents.
• The Event View, where you can monitor and cancel the execution of your TestEvents.

Enter:

• Agent Name (e.g., Agent2)
• Assign a Machine Name

This agent will be responsible for running your test event.

Step 4: Create and Configure a TestEvent (Tosca Commander)

• Open Tosca Commander
• Navigate to: Project > Execution > TestEvents
• Click Create TestEvent
• Provide a name like Sample

• Step 4.1: Assign Required ExecutionList
• Select the ExecutionList (this is where you define which test cases will run)
• Select an Execution Configuration
• Assign the Agent created in Step 3
• Step 4.2: Save and Copy Node Path
• Save the TestEvent

  

• TestEvent → Copy Node Path

  

• Paste this into the TestEvents field in Jenkins build step

  

Step 5: How the Integration Works

Execution Flow:

• Jenkins triggers test execution using ToscaCIClient.
• The request reaches the Tosca Distribution Server (ManagerService).
• Tosca Server coordinates with AOS to retrieve test data from the Common Repository.
• The execution task is distributed to a DEX Agent.
• DEX Agent runs the test cases and sends the results back.
• Jenkins build is updated with the execution status (Success/Failure).

Step 6: Triggering Execution via Jenkins

Once you’ve entered all required fields:

• Save the Jenkins job
• Click Build Now in Jenkins

What Happens Next:

• The configured DEX Agent will be triggered.
• You’ll see a progress bar and test status directly in the DEX Monitor.

  

• Upon completion, the Jenkins build status (Pass or failure) reflects the outcome of the test execution.

  

Step 7: View Test Reports in Jenkins

To visualize test results:

• Go to Manage Jenkins > Manage Plugins > Available
• Search and install Test Results Analyzer
• Once installed, configure Jenkins to collect results (e.g., via JUnit or custom publisher if using Tosca XML outputs)

Conclusion:

Integrating Tosca with Jenkins enhances your CI/CD workflow by automating test execution and reducing manual effort. This integration streamlines your development process and supports the delivery of reliable, high-quality software. By following the steps outlined in this guide, you can set up a smooth and efficient test automation pipeline that saves time and improves productivity. With testing seamlessly built into your workflow, your team can focus more on innovation and delivering value to end users.

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Frequently Asked Questions