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Since Selenium WebDriver is created for browser automation, it can be easily used for scraping data from the web. In this post we will consider some advantages. Best practises while using selenium 4. Toptal's guide to modern web scraping with selenium. And with that, hopefully, you too can make a simple web scraper using selenium 😎. If you enjoyed this post subscribe to my newsletter to get notified whenever I write new posts. Open to collaboration. I recently made a collaborations page on my website. This selenium tutorial is designed for beginners to learn how to use the python selenium module to perform web scraping, web testing and create website bots. In this article I will show you how it is easy to scrape a web site using Selenium WebDriver. I will guide you through a sample project which is written in C# and uses WebDriver in conjunction with the Chrome browser to login on the testing page and scrape the text from the private area of the website.

C# is still a popular backend programming language, and you might find yourself in need of it for scraping a web page (or multiple pages). In this article, we will cover scraping with C# using an HTTP request, parsing the results, and then extracting the information that you want to save. This method is common with basic scraping, but you will sometimes come across single-page web applications built in JavaScript such as Node.js, which require a different approach. We’ll also cover scraping these pages using PuppeteerSharp, Selenium WebDriver, and Headless Chrome.

Note: This article assumes that the reader is familiar with C# syntax and HTTP request libraries. The PuppeteerSharp and Selenium WebDriver .NET libraries are available to make integration of Headless Chrome easier for developers. Also, this project is using .NET Core 3.1 framework and the HTML Agility Pack for parsing raw HTML.

Part I: Static Pages

Setup

If you’re using C# as a language, you probably already use Visual Studio. This article uses a simple .NET Core Web Application project using MVC (Model View Controller). After you create a new project, go to the NuGet Package Manager where you can add the necessary libraries used throughout this tutorial.

In NuGet, click the “Browse” tab and then type “HTML Agility Pack” to find the dependency.

Install the package, and then you’re ready to go. This package makes it easy to parse the downloaded HTML and find tags and information that you want to save.

Finally, before you get started with coding the scraper, you need the following libraries added to the codebase:

Making an HTTP Request to a Web Page in C#

Imagine that you have a scraping project where you need to scrape Wikipedia for information on famous programmers. Wikipedia has a page with a list of famous programmers with links to each profile page. You can scrape this list and add it to a CSV file (or Excel spreadsheet) to save for future review and use. This is just one simple example of what you can do with web scraping, but the general concept is to find a site that has the information you need, use C# to scrape the content, and store it for later use. In more complex projects, you can crawl pages using the links found on a top category page.

Using .NET HTTP Libraries to Retrieve HTML

.NET Core introduced asynchronous HTTP request libraries to the framework. These libraries are native to .NET, so no additional libraries are needed for basic requests. Before you make the request, you need to build the URL and store it in a variable. Because we already know the page that we want to scrape, a simple URL variable can be added to the HomeController’s Index() method. The HomeController Index() method is the default call when you first open an MVC web application.

Add the following code to the Index() method in the HomeController file:

Using .NET HTTP libraries, a static asynchronous task is returned from the request, so it’s easier to put the request functionality in its own static method. Add the following method to the HomeController file:

Let’s break down each line of code in the above CallUrl() method.

This statement creates an HttpClient variable, which is an object from the native .NET framework.

If you get HTTPS handshake errors, it’s likely because you are not using the right cryptographic library. The above statement forces the connection to use the TLS 1.3 library so that an HTTPS handshake can be established. Note that TLS 1.3 is deprecated but some web servers do not have the latest 2.0+ libraries installed. For this basic task, cryptographic strength is not important but it could be for some other scraping requests involving sensitive data.

This statement clears headers should you decide to add your own. For instance, you might scrape content using an API request that requires a Bearer authorization token. In such a scenario, you would then add a header to the request. For example:

The above would pass the authorization token to the web application server to verify that you have access to the data. Next, we have the last two lines:

These two statements retrieve the HTML content, await the response (remember this is asynchronous) and return it to the HomeController’s Index() method where it was called. The following code is what your Index() method should contain (for now):

The code to make the HTTP request is done. We still haven’t parsed it yet, but now is a good time to run the code to ensure that the Wikipedia HTML is returned instead of any errors. Make sure you set a breakpoint in the Index() method at the following line:

This will ensure that you can use the Visual Studio debugger UI to view the results.

Download mac os x el capitan. You can test the above code by clicking the “Run” button in the Visual Studio menu:

Visual Studio will stop at the breakpoint, and now you can view the results.

If you click “HTML Visualizer” from the context menu, you can see a raw HTML view of the results, but you can see a quick preview by just hovering your mouse over the variable. You can see that HTML was returned, which means that an error did not occur.

Parsing the HTML

With the HTML retrieved, it’s time to parse it. HTML Agility Pack is a common tool, but you may have your own preference. Even LINQ can be used to query HTML, but for this example and for ease of use, the Agility Pack is preferred and what we will use.

Before you parse the HTML, you need to know a little bit about the structure of the page so that you know what to use as markers for your parsing to extract only what you want and not every link on the page. You can get this information using the Chrome Inspect function. In this example, the page has a table of contents links at the top that we don’t want to include in our list. You can also take note that every link is contained within an <li> element.

From the above inspection, we know that we want the content within the “li” element but not the ones with the tocsection class attribute. With the Agility Pack, we can eliminate them from the list.

We will parse the document in its own method in the HomeController, so create a new method named ParseHtml() and add the following code to it:

In the above code, a generic list of strings (the links) is created from the parsed HTML with a list of links to famous programmers on the selected Wikipedia page. We use LINQ to eliminate the table of content links, so now we just have the HTML content with links to programmer profiles on Wikipedia. We use .NET’s native functionality in the foreach loop to parse the first anchor tag that contains the link to the programmer profile. Because Wikipedia uses relative links in the href Anand mahindra twitter. attribute, we manually create the absolute URL to add convenience when a reader goes into the list to click each link.

Exporting Scraped Data to a File

The code above opens the Wikipedia page and parses the HTML. We now have a generic list of links from the page. Now, we need to export the links to a CSV file. We’ll make another method named WriteToCsv() to write data from the generic list to a file. The following code is the full method that writes the extracted links to a file named “links.csv” and stores it on the local disk.

The above code is all it takes to write data to a file on local storage using native .NET framework libraries.

The full HomeController code for this scraping section is below.

Part II: Scraping Dynamic JavaScript Pages

In the previous section, data was easily available to our scraper because the HTML was constructed and returned to the scraper the same way a browser would receive data. Newer JavaScript technologies such as Vue.js render pages using dynamic JavaScript code. When a page uses this type of technology, a basic HTTP request won’t return HTML to parse. Instead, you need to parse data from the JavaScript rendered in the browser.

Dynamic JavaScript isn’t the only issue. Some sites detect if JavaScript is enabled or evaluate the UserAgent value sent by the browser. The UserAgent header is a value that tells the web server the type of browser being used to access pages (e.g. Chrome, FireFox, etc). If you use web scraper code, no UserAgent is sent and many web servers will return different content based on UserAgent values. Some web servers will use JavaScript to detect when a request is not from a human user.

You can overcome this issue using libraries that leverage Headless Chrome to render the page and then parse the results. We’re introducing two libraries freely available from NuGet that can be used in conjunction with Headless Chrome to parse results. PuppeteerSharp is the first solution we use that makes asynchronous calls to a web page. The other solution is Selenium WebDriver, which is a common tool used in automated testing of web applications.

Using PuppeteerSharp with Headless Chrome

For this example, we will add the asynchronous code directly into the HomeController’s Index() method. This requires a small change to the default Index() method shown in the code below.

In addition to the Index() method changes, you must also add the library reference to the top of your HomeController code. Before you can use Puppeteer, you first must install the library from NuGet and then add the following line in your using statements:

Now, it’s time to add your HTTP request and parsing code. In this example, we’ll extract all URLs (the <a> tag) from the page. Add the following code to the HomeController to pull the page source in Headless Chrome, making it available for us to extract links (note the change in the Index() method, which replaces the same method in the previous section example):

Similar to the previous example, the links found on the page were extracted and stored in a generic list named programmerLinks. Notice that the path to chrome.exe is added to the options variable. If you don’t specify the executable path, Puppeteer will be unable to initialize Headless Chrome.

Using Selenium with Headless Chrome

If you don’t want to use Puppeteer, you can use Selenium WebDriver. Selenium is a common tool used in automation testing on web applications, because in addition to rendering dynamic JavaScript code, it can also be used to emulate human actions such as clicks on a link or button. To use this solution, you need to go to NuGet and install Selenium.WebDriver and (to use Headless Chrome) Selenium.WebDriver.ChromeDriver. Note: Selenium also has drivers for other popular browsers such as FireFox.

Add the following library to the using statements:

Now, you can add the code that will open a page and extract all links from the results. The following code demonstrates how to extract links and add them to a generic list.

Notice that the Selenium solution is not asynchronous, so if you have a large pool of links and actions to take on a page, it will freeze your program until the scraping completes. This is the main difference between the previous solution using Puppeteer and Selenium.

Conclusion

Web scraping is a powerful tool for developers who need to obtain large amounts of data from a web application. With pre-packaged dependencies, you can turn a difficult process into only a few lines of code.

One issue we didn’t cover is getting blocked either from remote rate limits or blocks put on bot detection. Your code would be considered a bot by some applications that want to limit the number of bots accessing data. Our web scraping API can overcome this limitation so that developers can focus on parsing HTML and obtaining data rather than determining remote blocks.

In the last tutorial we learned how to leverage the Scrapy framework to solve common web scraping problems.Today we are going to take a look at Selenium (with Python ❤️ ) in a step-by-step tutorial.

Selenium refers to a number of different open-source projects used for browser automation. It supports bindings for all major programming languages, including our favorite language: Python.

The Selenium API uses the WebDriver protocol to control a web browser, like Chrome, Firefox or Safari. The browser can run either localy or remotely.

At the beginning of the project (almost 20 years ago!) it was mostly used for cross-browser, end-to-end testing (acceptance tests).

Now it is still used for testing, but it is also used as a general browser automation platform. And of course, it us used for web scraping!

Selenium is useful when you have to perform an action on a website such as:

• Clicking on buttons
• Filling forms
• Scrolling
• Taking a screenshot

It is also useful for executing Javascript code. Let's say that you want to scrape a Single Page Application. Plus you haven't found an easy way to directly call the underlying APIs. In this case, Selenium might be what you need.

Installation

We will use Chrome in our example, so make sure you have it installed on your local machine:

• selenium package

To install the Selenium package, as always, I recommend that you create a virtual environment (for example using virtualenv) and then:

Quickstart

Once you have downloaded both Chrome and Chromedriver and installed the Selenium package, you should be ready to start the browser:

This will launch Chrome in headfull mode (like regular Chrome, which is controlled by your Python code).You should see a message stating that the browser is controlled by automated software.

To run Chrome in headless mode (without any graphical user interface), you can run it on a server. See the following example:

The driver.page_source will return the full page HTML code.

Here are two other interesting WebDriver properties:

• driver.title gets the page's title
• driver.current_url gets the current URL (this can be useful when there are redirections on the website and you need the final URL)

Locating Elements

Locating data on a website is one of the main use cases for Selenium, either for a test suite (making sure that a specific element is present/absent on the page) or to extract data and save it for further analysis (web scraping).

There are many methods available in the Selenium API to select elements on the page. You can use:

• Tag name
• Class name
• IDs
• XPath
• CSS selectors

We recently published an article explaining XPath. Don't hesitate to take a look if you aren't familiar with XPath.

As usual, the easiest way to locate an element is to open your Chrome dev tools and inspect the element that you need.A cool shortcut for this is to highlight the element you want with your mouse and then press Ctrl + Shift + C or on macOS Cmd + Shift + C instead of having to right click + inspect each time:

find_element

There are many ways to locate an element in selenium.Let's say that we want to locate the h1 tag in this HTML:

All these methods also have find_elements (note the plural) to return a list of elements.

For example, to get all anchors on a page, use the following:

Some elements aren't easily accessible with an ID or a simple class, and that's when you need an XPath expression. You also might have multiple elements with the same class (the ID is supposed to be unique).

XPath is my favorite way of locating elements on a web page. It's a powerful way to extract any element on a page, based on it's absolute position on the DOM, or relative to another element.

WebElement

A WebElement is a Selenium object representing an HTML element.

There are many actions that you can perform on those HTML elements, here are the most useful:

• Accessing the text of the element with the property element.text
• Clicking on the element with element.click()
• Accessing an attribute with element.get_attribute('class')
• Sending text to an input with: element.send_keys('mypassword')

There are some other interesting methods like is_displayed(). This returns True if an element is visible to the user.

It can be interesting to avoid honeypots (like filling hidden inputs).

Honeypots are mechanisms used by website owners to detect bots. For example, if an HTML input has the attribute type=hidden like this:

This input value is supposed to be blank. If a bot is visiting a page and fills all of the inputs on a form with random value, it will also fill the hidden input. A legitimate user would never fill the hidden input value, because it is not rendered by the browser.

That's a classic honeypot.

Full example

Here is a full example using Selenium API methods we just covered.

We are going to log into Hacker News:

In our example, authenticating to Hacker News is not really useful on its own. However, you could imagine creating a bot to automatically post a link to your latest blog post.

In order to authenticate we need to:

• Go to the login page using driver.get()
• Select the username input using driver.find_element_by_* and then element.send_keys() to send text to the input
• Follow the same process with the password input
• Click on the login button using element.click()

Should be easy right? Let's see the code:

Easy, right? Now there is one important thing that is missing here. How do we know if we are logged in?

We could try a couple of things:

• Check for an error message (like “Wrong password”)
• Check for one element on the page that is only displayed once logged in.

So, we're going to check for the logout button. The logout button has the ID “logout” (easy)!

We can't just check if the element is None because all of the find_element_by_* raise an exception if the element is not found in the DOM.So we have to use a try/except block and catch the NoSuchElementException exception:

Taking a screenshot

We could easily take a screenshot using:

Note that a lot of things can go wrong when you take a screenshot with Selenium. First, you have to make sure that the window size is set correctly.Then, you need to make sure that every asynchronous HTTP call made by the frontend Javascript code has finished, and that the page is fully rendered.

In our Hacker News case it's simple and we don't have to worry about these issues.

Waiting for an element to be present

Dealing with a website that uses lots of Javascript to render its content can be tricky. These days, more and more sites are using frameworks like Angular, React and Vue.js for their front-end. These front-end frameworks are complicated to deal with because they fire a lot of AJAX calls.

If we had to worry about an asynchronous HTTP call (or many) to an API, there are two ways to solve this:

• Use a time.sleep(ARBITRARY_TIME) before taking the screenshot.
• Use a WebDriverWait object.

If you use a time.sleep() you will probably use an arbitrary value. The problem is, you're either waiting for too long or not enough.Also the website can load slowly on your local wifi internet connection, but will be 10 times faster on your cloud server.With the WebDriverWait method you will wait the exact amount of time necessary for your element/data to be loaded.

This will wait five seconds for an element located by the ID “mySuperId” to be loaded.There are many other interesting expected conditions like:

• element_to_be_clickable
• text_to_be_present_in_element
• element_to_be_clickable

Scraping With Selenium

You can find more information about this in the Selenium documentation

Executing Javascript

Sometimes, you may need to execute some Javascript on the page. For example, let's say you want to take a screenshot of some information, but you first need to scroll a bit to see it.You can easily do this with Selenium:

Conclusion

I hope you enjoyed this blog post! You should now have a good understanding of how the Selenium API works in Python. If you want to know more about how to scrape the web with Python don't hesitate to take a look at our general Python web scraping guide.

Web Scraping Selenium

Selenium is often necessary to extract data from websites using lots of Javascript. The problem is that running lots of Selenium/Headless Chrome instances at scale is hard. This is one of the things we solve with ScrapingBee, our web scraping API

Selenium is also an excellent tool to automate almost anything on the web.

If you perform repetitive tasks like filling forms or checking information behind a login form where the website doesn't have an API, it's maybe* a good idea to automate it with Selenium,just don't forget this xkcd: