In this article, we will see how to extract structured information from web-page leveraging BeautifulSoup and CSS selectors.
- Web Scraping Using Beautifulsoup
- Web Scraping Using Python Beautifulsoup Github
- Web Scraping Using Python Beautiful Soup Using
- Web Scraping Using Python Beautifulsoup Interview
WebScraping with BeautifulSoup
Pulling the HTML out
BeautifulSoup is not a web scraping library per se. It is a library that allows you to efficiently and easily pull out information from HTML. In the real world, it is often used for web scraping projects.
- Steps involved in web scraping python beautifulsoup:- Send a request to the URL of a webpage which you want to access. Then the server will respond to the request.
- This technique is called web scraping or web harvesting or web data extraction. This article discusses the steps involved in web scraping using the implementation of a Web Scraping framework of Python called Beautiful Soup. Steps involved in web scraping: Send an HTTP request to the URL of the webpage you want to access.
BeautifulSoup is an amazing parsing library in Python that enables web scraping from HTML and XML documents. It creates parse trees that are helpful to extract the data easily. Beautiful Soup Is a Valuable Web Scraping Tool Beautiful Soup is a powerful Python screen scraper that gives you control over how your data comes through during scraping. It's a valuable business tool, as it can give you access to competitor's web data like pricing, market trends, and more.
So, to begin, we'll need HTML. We will pull out HTML from the HackerNews landing page using the
requests python package.
Parsing the HTML with BeautifulSoup
Now that the HTML is accessible we will use BeautifulSoup to parse it. If you haven't already, you can install the package by doing a simple
pip install beautifullsoup4. In the rest of this article, we will refer to
We now need to parse the HTML and load it into a
soup object is very handy and allows us to easily access many useful pieces of information such as:
Targeting DOM elements
You might begin to see a pattern in how to use this library. It allows you to quickly and elegantly target the DOM elements you need.
If you need to select DOM elements from its tag (
<span>, ….) you can simply do
soup.<tag> to select it. The caveat is that it will only select the first HTML element with that tag.
For example if I want the first link I just have to do
This element will also have many useful methods to quickly extract information:
This is a simple example. If you want to select the first element based on its
class it is not much more difficult:
And if you don't want the first matching element but instead all matching elements, just replace
This simple and elegant interface allows you to quickly write short and powerful Python snippets.
For example, let's say that I want to extract all links in this page and find the top three links that appear the most on the page. All I have to do is this:
BeautifulSoup is a great example of a library that is both easy to use and powerful.
You can do much more to select elements using BeautifulSoup. Although we won't cover those cases in this article, here are few examples of advanced things you can do:
- Select elements with regexp
- Select elements with a custom function (links that have Google in them for example)
- Iterating over siblings elements
We also only covered how to target elements but there is also a whole section about updating and writing HTML. Again, we won't cover this in this article.
Let's now talk about CSS selectors.
Why learn about CSS selectors if BeautifulSoup can select all elements with its pre-made method?
Well, you'll soon understand.
Sometimes, the HTML document won't have a useful class and id. Selecting elements with BS4 without relying on that information can be quite verbose.
For example, let's say that you want to extract the score of a post on the HN homepage, but you can't use
class name or
id in your code. Here is how you could do it:
Not that great right?
If you rely on CSS selectors, it becomes easier.
This is much clearer and simpler, right? Of course, this example artificially highlights the usefulness of the CSS selector. But, you will quickly see that the DOM structure of a page is more reliable than the class name.
Another thing that makes CSS selectors great for web scraping is that they are easily debuggable. I'll show you how. Open Chrome, then open your developers’ tools, (left-click -> “Inspect”), click on the document panel, and use “Ctrl-F or CMD-F” to be in search mode.
In the search bar, you'll be able to write any CSS expression you want, and Chrome will instantly find all elements matching it.
Iterate over the results by pressing
Enter to check that you are correctly getting everything you need.
What is great with Chrome is that it works the other way around too. You can also left-click on an element, click “Copy -> Copy Selector”, and your selector will be pasted in your clipboard.
CSS selectors, and particularly pseudo-classes, allow you to select any elements you want with one simple string.
Child and descendants
You can select direct child and descendant with:
And you can mix them together:
This will totally work.
Web Scraping Using Beautifulsoup
This one is one of my favorites because it allows you to select elements based on the elements on the same level in the DOM hierarchy, hence the sibling expression.
To select all
p coming after an
h2 you can use the
h2 ~ p selector (it will match two
p). You can also use
h2 + p if you only want to select
p coming directly after an
h2 (it will match only one
Attribute selectors allow you to select elements with particular attributes values. So,
p[data-test='foo'] will match
Position pseudo classes
If you want to select the last
p inside a section, you can also do it in “pure” CSS by leveraging position pseudo-classes. For this particular example, you just need this selector:
section p:last-child(). If you want to learn more about this, I suggest you take a look at this article
I also think that CSS expressions are easier to maintain. For example, at ScrapingBee, when we do custom web scraping tasks all of our scripts begins like this:
This makes it easy and quick to fix scripts when DOM changes appear. The laziest way to do it is to simply copy/paste what Chrome gives you when you left-click on an element. If you do this, be careful, Chrome tends to add a lot of useless selectors when you use this trick. So do not hesitate to clean them up a bit before using them in your script.
In the end, everything you do with pure CSS selectors you can do it with BeautifulSoup4. But, I think choosing the former is the best way to go.
Web Scraping Using Python Beautifulsoup Github
I hoped you liked this article about web scraping in Python and that it will make your life easier.
If you'd like to read more about web scraping in Python do not hesitate to check out our extensive Python web scraping guide.
You might also be interested by our XPath tutorial
Web Scraping Using Python Beautiful Soup Using
Web Scraping Using Python Beautifulsoup Interview
Pierre de Wulf