Content from What is Web Scraping?

Last updated on 2026-01-22 | Edit this page

Overview

Questions

  • What is web scraping and why is it useful?
  • What are typical use cases for web scraping?

Objectives

After completing this episode, participants should be able to…

  • Be able to navigate around a website, understanding the concept of structured data
  • Discuss how data can be extracted from web pages

What is web scraping?

Web scraping is a technique for extracting information from websites. This can be done manually but it is usually faster, more efficient and less error-prone to automate the task.

Web scraping allows you to acquire non-tabular or poorly structured data from websites and convert it into a usable, structured format, such as a .csv file or spreadsheet.

Scraping is about more than just acquiring data: it can also help you archive data and track changes to data online.

It is closely related to the practice of web indexing, which is what search engines like Google do when mass-analysing the Web to build their indices. But contrary to web indexing, which typically parses the entire content of a web page to make it searchable, web scraping targets specific information on the pages visited.

For example, online stores will often scour the publicly available pages of their competitors, scrape item prices, and then use this information to adjust their own prices. Another common practice is “contact scraping” in which personal information like email addresses or phone numbers is collected for marketing purposes.

Web scraping is also increasingly being used by scholars to create data sets for text mining projects; these might be collections of journal articles or digitised texts. The practice of data journalism, in particular, relies on the ability of investigative journalists to harvest data that is not always presented or published in a form that allows analysis.

Example: Scraping parliamentary websites for contact information

In this workshop, we will learn how to extract information from various web pages. Different webpages can have widely differing formats which will affect our decisions as to which method of scraping data might be appropriate.

Before we can make such decisions we need to have some understanding of the makeup of a webpage. Let’s start by looking at the list of members of the Canadian parliament, which is available on the Parliament of Canada website

This is how this page appears in December 2025:

Screenshot of the Parliament of Canada website (Top)Screenshot of the Parliament of Canada websitei (Bottom)

There are several features (circled in the image above) that make the data on this page easier to work with. The search, reorder, refine features and display modes hint that the data is actually stored in a (structured) database before being displayed on this page. The data can be readily downloaded either as a comma separated values (.csv) file or as XML for re-use in their own database, spreadsheet or computer program.

Even though the information displayed in the view above is not labelled, anyone visiting this site with some knowledge of Canadian geography and politics can see what information pertains to the politicians’ names, the geographical area they come from and the political party they represent. This is because human beings are good at using context and prior knowledge to quickly categorise information.

Computers, on the other hand, cannot do this unless we provide them with more information. If we examine the source HTML code of this page, we can see that the information displayed has a consistent structure:

HTML 

(...)
<tr role="row" id="mp-list-id-25446">
    <td data-sort="Allison Dean" class="sorting_1">
        <a href="/members/en/dean-allison(25446)">
            Allison, Dean
        </a>
    </td>
    <td data-sort="Conservative">Conservative</td>
    <td data-sort="Niagara West">
        <a href="/members/en/constituencies/niagara-west(1124)">Niagara West</a>
    </td>
    <td data-sort="Ontario">Ontario</td>
</tr>
(...)

Using this structure, we may be able to instruct a computer to look for all parliamentarians from Alberta and list their names and caucus information.

Callout

Structured vs unstructured data

When presented with information, human beings are good at quickly categorizing it and extracting the data that they are interested in. For example, when we look at a magazine rack, provided the titles are written in a script that we are able to read, we can rapidly figure out the titles of the magazines, the stories they contain, the language they are written in, etc. and we can probably also easily organize them by topic, recognize those that are aimed at children, or even whether they lean toward a particular end of the political spectrum. Computers have a much harder time making sense of such unstructured data unless we specifically tell them what elements data is made of, for example by adding labels such as this is the title of this magazine or this is a magazine about food. Data in which individual elements are separated and labelled is said to be structured.

Let’s look now at the current list of members for the UK House of Commons.

Screenshot of UK MP list webpage
Screenshot of the UK House of Commons website

This page also displays a list of names, political and geographical affiliation. There is a search box and a filter option, but no obvious way to download this information and reuse it.

Here is the code for this page:

HTML 

(...)
<a class="card card-member" href="/member/172/contact">
    <div class="card-inner">
        <div class="content">
            <div class="image-outer">
                <div class="image"
                     aria-label="Image of Ms Diane Abbott"
                     style="background-image: url(https://members-api.parliament.uk/api/Members/172/Thumbnail); border-color: #909090;"></div>
            </div>
            <div class="primary-info">
                Ms Diane Abbott
            </div>
            <div class="secondary-info">
                Independent
            </div>
        </div>
        <div class="info">
            <div class="info-inner">
                <div class="indicators-left">
                    <div class="indicator indicator-label">
                        Hackney North and Stoke Newington
                    </div>
                </div>

                <div class="clearfix"></div>
            </div>
        </div>
    </div>
</a>
(...)

We see that this data has been structured for displaying purposes (it is arranged in rows inside a table) but the different elements of information are not clearly labelled.

What if we wanted to download this dataset and, for example, compare it with the Canadian list of MPs to analyze gender representation, or the representation of political forces in the two groups? We could try copy-pasting the entire table into a spreadsheet or even manually copy-pasting the names and parties in another document, but this can quickly become impractical when faced with a large set of data. What if we wanted to collect this information for every country that has a parliamentary system?

Fortunately, there are tools to automate at least part of the process. This technique is called web scraping.

“Web scraping (web harvesting or web data extraction) is a computer software technique of extracting information from websites.” (Source: Wikipedia)

Web scraping typically targets one web site at a time to extract unstructured information and put it in a structured form for reuse.

Web scraping might not be necessary …

As useful as scraping is, there might be better options for the task. Choose the right (i.e. the easiest) tool for the job.

  • Check whether or not you can easily copy and paste data from a site into Excel or Google Sheets. This might be quicker than scraping.
  • Check whether there is data available on the website for download (you may need to search around the website to find this but it may save time overall).
    • For example, the UK Parliament website has a large library of data published for re-use.
  • Check if the site or service already provides an API to extract structured data. If it does, that will be a much more efficient and effective pathway.
  • For much larger needs, Freedom of information Act (FOIA) requests can be useful. Be specific about the formats required for the data you want.

… but if it is

In the next episodes, we will continue exploring the examples above and try different techniques to extract the information they contain.

Before we launch into web scraping proper however, we need to look a bit more closely at how information is organized within an HTML document and how to build queries to access a specific subset of that information.

References

Key Points
  • Humans are good at categorizing information, computers not so much.
  • Often, data on a web site is not properly structured, making its extraction difficult.
  • Web scraping is the process of automating the extraction of data from web sites.
  • Tools may be available on a web page which enable data to be downloaded directly.

Content from Anatomy of a web page

Last updated on 2026-01-28 | Edit this page

Overview

Questions

  • What’s behind a website, and how can I extract information from it?
  • How can I find the code for a specific element on a web page?

Objectives

After completing this episode, participants should be able to…

  • Identify the structure and key components of an HTML document
  • Explain how to use the browser developer tools to view the underlying html content of a web page
  • Use the browser developer tool to find the html code for specific items on a web page

Introduction

Before we delve into web scraping properly, we will first spend some time introducing some of the techniques that are required to indicate exactly what should be extracted from the web pages we aim to scrape.

Here, we’ll develop an understanding of how content and data are structured on the web. We’ll start by exploring what HTML (Hypertext Markup Language) is and how it uses tags to organise and format content. Then, we’ll look at how to view the HTML source code for a web page and look at how browser developer tools can be used to search for specific elements on a webpage.

HTML quick overview

All websites have a Hypertext Markup Language (HTML) document behind them. Below is an example of HTML for a very simple webpage that contains just three sentences. As you look through it, try to imagine how the website would appear in a browser.

HTML 

<!DOCTYPE html>
<html>
<head>
  <title>Sample web page</title>
</head>
<body>
  <h1>h1 Header #1</h1>
  <p>This is a paragraph tag</p>
  <h2>h2 Sub-header</h2>
  <p>A new paragraph, now in the <b>sub-header</b></p>
    <h1>h1 Header #2</h1>
    <p>
    This other paragraph has two hyperlinks,
    one to <a href="https://carpentries.org/">The Carpentries homepage</a>,
    and another to the
    <a href="https://carpentries.org/workshops/past-workshops/">past workshops</a> page.
  </p>
</body>
</html>

This text has been saved with a .html extension, SampleWebpageCode.html. If you open it in your web browser, the browser will interpret the markup language and display a nicely formatted web page as below.

Screenshot of a simple website with the previews HTML

When you open an HTML file in your browser, what it’s really doing is reading a structured document made up of elements, each marked by tags inside angle brackets (< and >). For instance, the HTML root element, which delimits the beginning and end of an HTML document, is identified by the <html> tag.

Most elements have both an opening tag and a closing tag, which define the start and end of that element. For example, in the simple website we looked at earlier, the head element begins with <head> and ends with </head>.

Because elements can be nested inside one another, an HTML document forms a tree structure, where each element is a node that can contain child nodes, as illustrated in the image below.

Screenshot of a simple website with the previews HTML
The Document Object Model (DOM) that represents an HTML document with a tree structure. Source: Wikipedia. Author: Birger Eriksson

Finally, we can define or modify the behaviour, appearance, or functionality of an element using attributes. Attributes appear inside the opening tag and consist of a name and a value, formatted like name="value".

For example, in the simple website, we added a hyperlink using the <a>...</a> tags. To specify the destination URL, we used the href attribute inside the opening <a> tag like this: <a href="https://carpentries.org/workshops/past-workshops/">past workshops</a>.

Here is a non-exhaustive list of common HTML elements and their purposes:

  • <hmtl>...</html>: The root element that contains the entire document.
  • <head>...</head>: Contains metadata such as the page title that the browser displays.
  • <body>...</body>: Contains the content that will be shown on the webpage.
  • <h1>...</h1>, <h2>...</h2>, <h3>...</h3>: Define headers of levels 1, 2, 3, and so on.
  • <p>...</p>: Represents a paragraph.
  • <a href="">...</a>: Creates a hyperlink; the destination URL is set with the href attribute.
  • <img src="" alt="">: Embeds an image, with the image source specified by src and alternative text provided by alt. It doesn’t have an opening tag.
  • <table>...</table>, <th>...</th>, <tr>...</tr>, <td>...</td>: Define a table structure, with headers (<th>), rows (<tr>), and cells (<td>).
  • <div>...</div>: Groups sections of HTML content together.
  • <script>...</script>: Embeds or links to JavaScript code.

In the list above, we mentioned some attributes specific to hyperlink (<a>) and image (<img>) elements, but there are also several global attributes that most HTML elements can have. These are especially useful for identifying elements when web scraping:

  • id="": Assigns a unique identifier to an element; this ID must be unique within the entire HTML document.
  • title="": Provides extra information about the element, shown as a tooltip when the user hovers over it.
  • class="": Applies a common styling or grouping to multiple elements at once.

This A to Z List gives a comprehensive list of html tags.

CSS (Cascading Style Sheets) is code which allows the way that a web page is displayed (colours, fonts etc) to be separated from the content. It allows the same styles to be applied to a set of HTML documents without the need to specify them in each document.

CSS uses rule sets which are applied to the HTML elements using selectors.

You may see selectors applied to HTML elements by tag, class or ID. These may be useful for targeting elements when web scraping. The CSS rules may be applied using a

tag in the HTML file or may be in a separate .css file linked from the HTML file.

An example of two style rules applied to our HTML example are shown below. They can be viewed by opening the WebpageCSS.html file.

HTML 

<!DOCTYPE html>
<html>
<head>
  <title>Sample web page</title>
  <style>
        /* CSS Rule */
        h1 {
            color: blue;
            /* Property: value */
            font-size: 24px;
        }

        p {
            color: green;
            font-size: 16px;
        }
    </style>
</head>
<body>
  <h1>h1 Header #1</h1>
  <p>This is a paragraph tag</p>
  <h2>h2 Sub-header</h2>
  <p>A new paragraph, now in the <b>sub-header</b></p>
    <h1>h1 Header #2</h1>
    <p>
    This other paragraph has two hyperlinks,
    one to <a href="https://carpentries.org/">The Carpentries homepage</a>,
    and another to the
    <a href="https://carpentries.org/workshops/past-workshops/">past workshops</a> page.
  </p>
</body>
</html>

For more information this CSS Introduction and CSS Cheat Sheet provide a good starting point.

To summarize: elements are identified by tags, and attributes let us assign properties or identifiers to those elements. Understanding this structure will make it much easier to extract specific data from a website.

Inspecting the web page source code

We will use the HTML code that describes this very page you are reading as an example. By default, a web browser interprets the HTML code to determine what markup to apply to the various elements of a document, and the code is invisible. To make the underlying code visible, all browsers have a function to display the raw HTML content of a web page.

Challenge

Exercise: Display the source of this page

Using your favourite browser, display the HTML source code of this page.

Tip: in most browsers, all you have to do is do a right-click anywhere on the page and select the “View Page Source” option (“Show Page Source” in Safari).

Another tab should open with the raw HTML that makes this page. See if you can locate its various elements, where the head and body elements start and end. See if you can pickout this challenge box in particular.

You will see that this webpage is quite complex and it may not be easy to pick out the elements that you are looking for. Many webpages are automatically generated and may not be laid out in the straightforward manner of our initial, very simple, example.

Try searching for head> or body> to locate both the start and end of these sections.

Even though these may be difficult to locate, you will see that the same overall structure is still used for the webpage.

The HTML structure of the page you are currently reading looks something like this (most text and elements have been removed for clarity):

HTML 

<!doctype html>
<html lang="en" data-bs-theme="auto">
  <head>
    (...)
    <title>Introduction to Web Scraping: Anatomy of a web page</title>
    (...)
  </head>
  <body>
	 (...)
  </body>
</html>

We can see from the source code that the title of this page is in a title element that is itself inside the head element, which is itself inside an html element that contains the entire content of the page.

Say we wanted to tell a web scraper to look for the title of this page, we would use this information to indicate the path the scraper would need to follow as it navigates through the HTML content of the page to reach the title element. We can search for specific items in the source page code using the built in developer console.

Callout

Display the console in your browser

  • In Firefox, use the More Tools > Web Developer Tools menu item.
  • In Chrome, use the More tools > Developer tools menu item.
  • In Safari, use the Develop > Show Error Console menu item. If your Safari browser doesn’t have a Develop menu, you must first enable this option in the Preferences, see above.

Here is how the console looks like in the Chrome browser:

Screenshot of Chrome developer console
Developer console in Chrome

By default the console will probably open in the Console tab. For now, don’t worry too much about error messages if you see any in the console when you open it. We will be using the Elements tab to locate specific items in the web page.

Locate code for specific elements

To find the code for a specific item on a web page, hover over it and right click, selecting Inspect from the dialog displayed (shown below).

Dialog with Inspect option
Dialog to select element inspection in Chrome

This will automatically move to the Elements tab in the developer console (opening the developer console if not already open) and display the section of code for the selected element. The specific line of code for the element will be highlighted. In the example below a name was selected on the Canadian MPs webpage resulting in the code below:

Code shown in the developer console for a selected element
Code for selected element, displayed in the developer console

Conversly, by hovering over a line of code in the Elements tab, the corresponding element will be highlighted on the web page, showing the tag and size of the element. This is shown below:

Screenshot of element highlighted on web page
Element hightlighted by hovering over code
Challenge

Identify element tag for extracting MP names

Go back to the UK House of Commons webpage. Use the developer console to identify what you might need to search for in order to extract a list of MPs names.

Can you see an issue with the data collected if you just searched on this particular page?

The class “primary-info” contains the text for the names.

Note that this information is spread over several pages. It may be necessary to make use of the links for further pages in order to extract all of the required information.

Dynamic websites

We are not going to cover these in detail in this lesson but you should be aware of dynamic websites and how the HTML code observed might differ between these and a static website with no interactive elements.

Visit this practice webpage created by Hartley Brody for learning and practicing web scraping: Oscar Winning Films (but first, read the terms of use). Select “2015” to display that year’s Oscar-winning films.

Now try viewing the HTML behind the page using the View Page Source tool in your browser.

Discussion

Challenge

Can you find the Best Picture winner Spotlight anywhere in the HTML?

Can you find any of the other movies or the data from the table?

If not, how could you scrape this page?

When you explore a page like this, you’ll notice that the movie data (including the title Spotlight) isn’t present in the initial HTML source. That’s because the website uses JavaScript to load the information dynamically. JavaScript is a programming language that runs in your browser and allows websites to fetch, process, and display content on the fly — often in response to user actions, like clicking a button.

When you select “2015”, your browser runs JavaScript (triggered by one of the <script> elements in the HTML) to retrieve the relevant movie information from the web server and dynamically update the table. This makes the page feel more interactive, but it also means that the initial HTML you see doesn’t contain the movie data itself.

You can observe this difference when using the “View page source” and “Inspect” tools in your browser: “View page source” shows the original HTML sent by the server, before any JavaScript runs. “Inspect” shows the rendered HTML, after JavaScript has executed and updated the page content.

Key Points
  • Every website is built on an HTML document that structures its content.
  • An HTML document is composed of elements, usually defined by an opening and a closing .
  • Elements can have attributes that define their properties, written as .
  • CSS may be used to control the appearance of the rendered webpage.
  • Dynamic webpages may have content which isn’t loaded until the item is selected.

Content from Manually scrape data using browser extensions

Last updated on 2026-01-22 | Edit this page

Overview

Questions

  • How can I get started scraping data off the web?
  • How do I assess the most appropriate method to scrape data?

Objectives

After completing this episode, participants should be able to…

  • Understand the different tools for accessing web page data
  • Use the WebScraper tool to extract data from a web page
  • Assess the appropriate method for gathering the required data

Using the Web Scraper Chrome extension

Now we are finally ready to do some web scraping using Web Scraper Chrome extension. If you haven’t it installed on your machine, please refer to the Setup instructions.

For this lesson, we will again be using the UK Members of Parliament webpages. We are interested in scraping a list of MPs and their constituencies with the help of Web Scraper.

First, let’s focus our attention on the first webpage with the list of MPs.
We are interested in downloading the list of MP’s names and their constituency.

Screenshot of UK MP list webpage
Screenshot of the UK MP list website

There are two ways of using Web Scraper, either using the Wizard GUI or using selectors in the developer tools. The wizard gives an easy to use interface but may be less flexible and doesn’t provide the ability to customise that is possible using the developer tools.

Using the Web Scraper wizard

With the extension installed the Wizard window can be opened by selecting the Web Scraper icon on the browser toolbar:

Screenshot of Web Scraper wizard dialog
Web Scraper Wizard

The wizard allows you to select any links to navigate to other pages. In our example we don’t need to do this so we will select Skip In the Page Navigation Type tab, select whether to make selections from the listing page or whether to open links

  • We will use the Listing page option
  • Select Continue - this will auto-generate selectors and give a preview of the data

The image below shows an example of the data which is automatically extracted from this web page without any selection:

Screenshot of automatically scraped MP data
Automatically scraped MP data

Note that this has only gathered the names of MPs for one page, collecting about 20 entries out of a total of 650. The next section Pagination & Scroll allows multiple pages to be selected for scraping:

  • Choose Select Next Page button
  • Select the appropriate means of selecting more pages. This could be either a set of numbered pages or a ‘next page’ button. Several buttons can be selected if needed.
  • On completion click the green Done selecting button.
Screenshot of pagination selection
Pagination & Scroll selection

On selection of the Finish button the dialog will show that scraper configuration is ready and the Scrape the page button can be selected.

Now data has been scraped for all 650 MPs from all pages:

Screenshot showing data from multiple pages
Data scraped from multiple pages

The data scraped can now be downloaded as either a .xlsx or .csv file.

Using Web Scraper with the browser developer console

  • Open the Developer Tools and open the Web Scraper tab
    • If the developer tools are docked at the side of the screen use the three dots a the top right of the dialog and select the option to dock at the bottom (see below)
    Dialog showing how to select developer tools docking position
    Dialog to select Developer Tools docking position

The Web Scraper extension works on a “Sitemap”. The previous exercise will already have created a sitemap and this will be listed in the opening window on the tab. Alternatively, a new sitemap can be created: - Select Create new sitemap-> Create Sitemap - Add a Sitemap name and Start URL for the webpage you wish to scrape - Click Create Sitemap

When a sitemap has been created then selectors can be created to govern how the webpage will be scraped. For a webpage created by the Wizard, the selectors generated automatically can be inspected, edited and new selectors created as required.

It is a good idea to spend some time navigating the website and taking a look at the underlying code, using the Inspect facility, to decide on the best way to set up the selectors. The code will show the type of elements underlying the items on the webpage and may help with deciding how to scrape the page.

The MP information data is spread across several pages. The first selector that we will create will enable the scraper to automatically scrape multiple pages.

  • Select the Add new selector button. In the resulting dialog:
    • Choose an Id for the selector, e.g. Paging
    • The type menu offers a drop down menu of available selectors. In this case, we will choose the Pagination selector
    • Use the Select button to select the relevant elements on the webpage. In this case the pagination uses the numbered boxes at the top or bottom of the page. More than one selection can be made by using Shift+Enter. In the example shown below, just two pages have been selected.
    • The Element Preview button can be used to check that the correct items have been selected.
    • The Data Preview button will show the data that will result from this scraping operation.
Screenshot of creating pagination selector
Creating a Pagination selector

The information to be scraped is on the page navigated to by selecting one of the MP list boxes. We will set up a selector to select each box on the page. Note that, because the pagination selector has already been set up, it is only necessary to do this for one page.

The next information to be selected is on the page arrived at by the links selected in the previous step. By clicking on the selector just created in the list it can be seen that the link breadcrumbs update:

  • Select the Paging row in the dialog
  • Create a new selector as before, this time choosing a Link selector
  • When using the Select button all MP list boxes can be selected by clicking on a second box.
  • Check the Multiple option
Screensho of creating link selector
Creating a Link Selector

Again, the next information to be selected is on the page arrived at by the links selected in the previous step. By clicking on the select-mp selector in the list it can be seen that the link breadcrumbs have again been updated:

Screenshot showing link breadcrumbs
Breadcrumbs for scraped pages

We now need to navigate to one of the MP pages by clicking on one of the list boxes. The required data can now be gathered by adding more selectors.

  • Create a Text type selector
  • Select the field containing the name
Screenshot of text selector creation
Creating a Text selector to find the MP name

We can use the same method to create a selector for the email address. There should now be two selectors within the select-mp page.

Name and email selectors
Name and email selectors

The sitemap is now ready for scraping. Select Sitemap name -> Scrape. The Request interval and Page load delay options can be left at the default 2000ms. Clicking the Start scraping button will start the scraping process. A window will open, showing the pages being accessed in the scraping process.

On completion of scraping it may be necessary to click the Refresh button in order to view the data. A table will be displayed showing the data extracted. The Sitemap name -> Export Data option allows export in either .xlsx or .csv format.

MP-data.xlsx is the file downloaded after the scraping exercise described above. On examination of this file, it can be seen that all of the MP’s names have been extracted but the list of email addresses is incomplete.

Challenge

Challenge

MP-data.xlsx is the file downloaded after the scraping exercise described above. On examination of this file, it can be seen that all of the MP’s names have been extracted but the list of email addresses is incomplete.

Why do you think that there are some email addresses missing? - Take a look at the code for the email address information. - Compare the information for MPs where the email address was found and where it was not

The code for the email address on the Ms Diane Abbott page is shown below:

HTML 

(...)
<div class="col-md-7">
   <div class="contact-line">
      <span class="label">Phone Number:</span> 
      <a href="tel:020 7219 4426">020 7219 4426</a>
   </div>
   <div class="contact-line">
      <span class="label">Email Address:</span> 
      <a href="mailto:diane.abbott.office@parliament.uk"> diane.abbott.office@parliament.uk</a>
   </div>                   
</div>
(...)

If we look at the selector code: “div.contact-line:nth-of-type(2) a” we can see that looks like it has picked out the second “contact-line” class and then used the text from the “a” tag. If we look at the similar section of code for an MP with just an email address in the contacts (no phone number) then we can see that a selector which searches for the second element will not yield a result.

Web Scraper includes some extra functionality which allows a more explicit search to be carried out using JQuery selectors. It is beyond the scope of this lesson to cover this in detail. There is information in the Web Scraper JQuery Selectors documentation.

We will look at how to use the contains option to extract the complete list of email addresses.

Using JQuery to refine selector options

The JQuery contains value can be used to target elements which contain a particular string. Inspection of the “contact-line” class shows that the email address item contains the string “Email Address”. The selector can be edited manually to

div.contact-line:contains(‘Email Address’) a

This will now only target the contact-line elements which contain the “Email Address” text.

Inspection of the new downloaded spreadsheet shows that all of the emails have now been extracted.

Discussion

Challenge

Modify your sitemap to also gather the phone number information for each MP

Key Points
  • Data that is relatively well structured (in a table) is relatively easily to scrape.
  • More often than not, web scraping tools need to be told what to scrape.
  • JQuery can be used to define more precisely what information is to be scraped.