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Selenium Web Scraping | How Good This Tool Is and Ways to Use It

If you are interested in how to extract data from websites, you might have heard about Selenium, a Python library, and tool. It's a web browser automation tool for web applications.

The tool enables you to open a web browser and perform various tasks, such as entering various details in forms and clicking buttons. You can also use it to look for particular information from web pages and add and delete data.

In this guide, we'll look at how to use Selenium for web scraping.

Web Scraping With Selenium

Selenium will help you extract valuable data from an otherwise unavailable web page.

The data can help you in various instances, including market research and price comparison that offers your business a competitive edge.

Web scraping is an efficient data collection method compared to surveys, focus groups, questionnaires, and other data collection methods. It helps you use HTML code to process web pages to extract data.

You can manipulate the scraped data from HTML pages and store it in a database.

Before you can scrape data from a website, it'll be helpful to check its terms of service as some websites may not allow web scraping. Additionally, a website can ban your IP address if you scrape data maliciously.

Web Scraping Static and Dynamic Web Pages

Web scraping requires you to understand the difference between static and dynamic web pages.

The page content remains the same in static web pages unless someone changes it manually.

Alternatively, the dynamic web page content can change depending on the site visitor. The content can change from one visitor to the other depending on the visitor's user profile.

While static web pages render on the server-side, a dynamic web page can render on the client-side, enhancing its time complexity.

Dynamic web content is generated per request after the initial load request. On the other hand, static content is generated locally, and the script is helpful in data collection.

static and dynamic pages graphic illustration

So, how do you use Selenium to extract data from a web page?

When scraping websites, Selenium provides some locators that help you identify the desired content from a web page. The standard locators refer to keywords used for particular HTML pages.

If you want to use Selenium for web scraping, you can use the following steps:


You can install Selenium using pip and using Conda.

Download Google Chrome WebDriver

Downloading and installing a web driver is an essential part of this process. The web driver will help you open your browser and access your desired website.

The download and installation process can vary depending on your choice of browser. Selenium supports various browsers, including Google Chrome, Internet Explorer, OperaFirefox, and safari.

tools key on the keyboard

In this guide, we'll use the Google Chrome browser.

You can download the Chrome web driver at https://chromedriver.chromium.org/downloads.

There are various methods of downloading Chrome, depending on the version you are using. One of the methods involves downloading the chrome drivers using the following link https://chromedriver.chromium.org/downloads.

To know the version of Chrome you have on your device, you should go to the top right corner of your browser window and click on the three vertical dots. From the drop-down menu that appears, scroll down to "Help" and then select "About Google Chrome." The process will show you your chrome version.

After downloading Chrome, web driver, and the Selenium package, you should proceed to launch the browser.

You can launch Chrome in a headful mode like the regular Chrome browser that you control using your Python. You'll get a message that automated software is controlling the browser.

Alternatively, you can run Chrome as a headless browser without a graphical user interface.

Some Webdriver properties include:

  • driver.page_source: it returns the full page HTML code

  • driver.title: gives you the title of the web page

  • driver.current_URL: provides the current URL. The property is essential when you have other redirections on the site, and you require the final URL

Finding Elements

One of the vital uses of Selenium is helping to find particular data on a website. Python web scraping helps extract data and save it for more manipulation and analysis. You can also use it as a test suite to confirm whether a particular element is present or absent on a page.

Some of the Selenium API methods you can use to select multiple elements on a page include:

  • Class name

  • Xpath

  • IDs

  • CSS selectors

  • Class name

CSS selectors window

For instance, you can use the following methods to locate HTML elements

  • find_elements_by_class_name

  • find_elements_by_css_selector

  • find_elements_by_tag_name

  • find_elements_by_xpath

  • find_elements_by_partial_link_text

  • find_elements_by_link_text

  • find_elements_by_name

If you locate one element, you should remove the "s" in elements. For instance, you should have:

  • find_element_by_name

  • find_element_by_xpath

  • find_element_by_tag_name

  • find_element_by_css_selector

  • find_element_by_partial_link_text

  • find_element_by_class_name

An Xpath language uses path expressions to take a set of nodes in an XML document.

How do you locate an element in Selenium?

For instance, if you want to locate an h1 tag on an HTML page, you can use the following methods:

  • h1 = driver.find_element_by_name( 'h1')

  • h1= driver.find_element_by_xpath('//h1')

  • h1= driver.find_element_by_class_name( 'someclass')

  • h1 = driver.find_element_by_id( 'great')

python selenium in use

You may not access some elements using a simple class or ID. In such an instance, you require an XPath expression. If you have a couple of elements in the same category, the ID should be uniquely selected.

XPath is a powerful way of extracting elements on a web page.

Extract Data Using Selenium

To extract data using Selenium, you should start by importing the libraries.

Selenium import webdriver

from selenium.webdriver.common.keys import pandas as pd

You should specify the path of the installed Chrome WebDriver.

driver = webdriver.Chrome (r"c: UsersEugeniDownloadschromedriver_win32chromedriver,exe")

Use the URL for the web page you want to scrape.

When you extract your data, you can export it into a CSV file or save it in a data frame.

Extract Data graphic icon

Is Selenium Suitable for Web Scraping?

Selenium is well known as automated test software. You can also use it for web scraping to collect valuable data from a website.

A WebDriver uses a browser to access your desired websites. Therefore, it's no different from accessing the internet by a robot or a human being. When you use a WebDriver to access a web page, the browser loads all the site's resources, including CSS files, JavaScript files, and images.

The browser also stores all the cookies.

If you use a program that sends handcrafted requests to the server, carrying out all the tasks will be challenging.

Selenium helps carry out various tasks, including screenshot retrieval, automated testing, and cookie retrieval.

Other uses of Selenium include data addition and deletion, form submission, auto-login, and alert handling.

Selenium is helpful for web scraping, which is an effective and reliable data collection method.

a person with laptop

Disadvantages of Using Selenium for Data Extraction

Some disadvantages of using Selenium for data scraping include:

  • Data extraction can be easily detected by simple scraping detection mechanisms like Google Analytics

  • When you use a browser to extract data from a site, you load the whole browser onto the system, consuming massive system resources and time. It can also cause your system security to overreact and even prevent the program from running.

  • Web scraping using a WebDriver can take longer than making a simple HTTP request to the server. The delay is because the WebDriver has to wait for the whole web page to load

  • Browsers download several files that may not be helpful for you, such as JS and CSS files. Different HTTP requirements can lead to an extensive network of traffic generated.

Which Is the Better Option Between Selenium and Beautiful Soup?

While Beautiful Soup is a valuable Python library for scraping structured HTML and XML data, Selenium is a general-purpose rendering tool.

So, how do the two differ?

Selenium is better for dynamic web scraping and data extraction from more complex pages. Web scraping using Selenium also takes longer as it has to wait for client-side technologies such as JavaScript to load.

On the other hand, Beautiful Soup has limitations on the websites it can scrape, and it's better suited for smaller projects. Since it just scraps the page source, it's faster than Selenium.

web scraping graphic illustration

Additionally, Beautiful Soup is easier to use than Selenium. You can start extracting data from a web page using Beautiful Soup with just a few lines of code. On the other hand, Selenium works as a headless browser. It can function as a web automation kit that involves filling out forms and mouse clicks. Thus, it has a more challenging learning curve than Beautiful Soup.

Beautiful Soup mainly helps in scraping data from static pages. Since it only looks at the page source, it's not prone to frontend-design changes. Selenium primarily interacts with dynamic content and pages. Therefore, it's more prone to superficial frontend design changes that can affect the scraping process.

If you want to extend Selenium's bindings, a Selenium wire comes in handy. It helps you to inspect various requests made by the browser.


Selenium allows you to extract valuable data from websites. The data helps you in various tasks such as market research that helps you in better decision making. Selenium mainly supports dynamic pages, while Beautiful Soup supports static web page content.

About Dusan Stanar

I'm the founder of VSS Monitoring. I have been both writing and working in technology in a number of roles for dozens of years and wanted to bring my experience online to make it publicly available. Visit https://www.vssmonitoring.com/about-us/ to read more about myself and the rest of the team.

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