Comparison of Screenshots in Python Before and After Scrolling

What will you learn?

In this tutorial, you will master the art of comparing screenshots taken before and after scrolling in Python. By leveraging Selenium for capturing screenshots and Pillow for image comparison, you’ll automate the process of visual validation with precision.

Introduction to the Problem and Solution

Visual comparison plays a crucial role in assessing web pages or applications accurately. When it comes to comparing screenshots before and after a scroll event, Python offers a powerful solution. By combining Selenium for screenshot capture and Pillow for image analysis, we can automate the comparison process effectively.

To tackle this challenge, we will craft a Python script that executes the following steps: – Utilize Selenium to launch a webpage. – Capture an initial screenshot before any scrolling. – Simulate scrolling actions on the webpage. – Capture another screenshot after scrolling. – Employ Pillow (PIL) library to compare both screenshots pixel by pixel.


# Import necessary libraries
from selenium import webdriver
from PIL import ImageChops, Image

# Open a browser window using Selenium
driver = webdriver.Chrome()

# Take screenshot before scrolling
before_scroll = driver.get_screenshot_as_png()

# Perform scrolling actions on the page

# Take screenshot after scrolling
after_scroll = driver.get_screenshot_as_png()

# Load screenshots using Pillow library for image comparison
img1 =
img2 =

# Compare images pixel by pixel for equality check
diff_image = ImageChops.difference(img1, img2)

if diff_image.getbbox():
    # Images are different - perform further actions here if needed

    # Save difference image or display it as per requirement


# Copyright PHD

(Note: Ensure selenium and pillow packages are installed using pip)


After launching a browser window via Selenium, two screenshots are captured – one pre-scrolling and one post-scrolling. These images are then processed using Pillow to facilitate pixel-by-pixel comparison through ImageChops.difference(). This method enables precise identification of any visual variances between the screenshots.

This approach empowers us to programmatically verify dynamic changes on webpages post user interactions or updates, facilitating automated testing scenarios requiring visual validations.

    How accurate is image comparison in detecting differences?

    Image comparison is remarkably accurate but sensitive; even slight pixel variations can trigger differences.

    Can I use this method for dynamic content verification?

    Absolutely! This method is ideal for verifying dynamic content changes through meticulous image comparisons.

    What happens if there is no difference between images?

    If no discrepancies are detected, it indicates that both screenshots are visually identical.

    Does this method work across different browsers?

    Yes! This technique is browser-agnostic as long as Selenium supports your chosen browser.


    In conclusion, mastering the art of comparing screenshots before and after scrolling in Python equips you with a robust tool for automating visual validation of web pages or applications. This technique proves invaluable in ensuring expected changes occur dynamically during user interactions or website updates.

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