Web Scraping with Beautiful Soup and Requests

The lesson introduces Beautiful Soup and Requests in Python for web scraping, with a focus on importing packages and retrieving HTML.

### Introduction to Web Scraping with Beautiful Soup and Requests in Python
* 🐍 Beautiful Soup and Requests are essential Python packages for web scraping, enabling beginners to **extract desired information from websites**.
* 📦 While there are more advanced packages available, this beginner series focuses on **Beautiful Soup and Requests**, with future series exploring **advanced functionalities**.
* 📥 The first step is to import these packages by using **`from bs4 import BeautifulSoup`** and **`import requests`**.
* 🌐 The next task is to specify the **URL from which the HTML data will be extracted** and assign it to a variable.
* 🔗 Using `requests.get(URL)` sends a get request to the URL and returns a response object, with a status code of **200 indicating success**.
* 🥣 Beautiful Soup is then used to **parse the raw HTML content** obtained from the URL, making it easier to **navigate and extract specific information**.
* 🔍 In the upcoming lessons, querying HTML elements such as tags, variable strings, and classes using **`find`** and **`find_all`** will be covered.
* 📊 The final lesson will involve a **mini project** to **extract data from a webpage** and **store it in a Pandas DataFrame**.

hello everybody. In this lesson, we're going to be taking a look at Beautiful Soup and Requests. Now, these packages in Python are really useful. These are the two main ones that I used when I was first starting out with web scraping. It can get a lot of what you want done in order to get that information out. Now, of course, there are other packages that you can use that may be a little bit more advanced. But again, this is just the beginner series. In a future series, we'll look at other packages as well that have some more advanced functionality. So what we're going to be doing is we're going to import these packages and then we're going to get all of the HTML from our website and make sure that it's in a usable state. And then in the next lesson, we're going to kind of query around in the HTML, kind of pick and choose exactly what we want. We'll look at things like tags, variable strings, classes, attributes, and more. So let's get started by importing our packages. What we're going

to say is from bs4. This is the module that we're taking it from. We're going to say import, and then we'll do beautiful soup. Then we're going to come down, and we're going to say import requests. Now let's go ahead and run this and hit shift enter, and it works well for me. Now if this does not work for you, you may potentially need to actually install bs4. So you may have to go to your terminal window and say pip install bs4. I'll just let you Google how to do that if you need to do that because it's pretty easy. But if you're using Jupyter notebooks through Anaconda like how we set it up at the beginning of this Python series, then you should be totally fine. It should be there for you. The next thing that we need to do is specify where we're taking this HTML from. So what we need to actually do is come right over here to our web page, and we need to get the URL. So we're going to go here.

going to copy this URL, and I'm just going to put it right here for a second. And what we're going to do is we're going to be using this URL quite a bit, so we just want to assign it to a variable. So to say, URL is equal to, and then we'll put it right in here. Now we can get rid of that. So now this is our URL going forward. This is where we'll be pulling data from. Let's go ahead and run this. Now we're going to use requests, and what we're going to do is we're going to say requests.get, and then we're going to put in URL. Now this get function is going to use the requests library. It's going to send a get request to that URL, and it's going to return a response object. Let's go ahead and run this. As you can see here, I got a response of 200. If you got something like a 204, or a 400, or 401, or 404, all of these things are potentially bad. Something like a 204

would mean there was no content in the actual web page. 400 means a bad request so it was invalid. The server couldn't process it and you don't get any response. If you got a 404, that might be one that you're familiar with. That's an error that means the server cannot be found. The next thing that we're going to do is take the HTML. Now if you remember, we come right back here and we inspect this. We have all of this HTML right here. Now on this web page specifically right now, it's completely static. It's not a bunch of moving stuff or anything like that. But usually when you're looking at HTML, if you're looking at something like Amazon, and those web pages can update, but when you actually pull that into Python, you're basically getting a snapshot of the HTML at that time. So what we're going to do is bring in all of this HTML, which is our snapshot of our website, and then we can take a look at it. So we're going to come right down here and now we're going to

say beautiful soup. So now we'll use the Beautiful Soup package or library. So when you say Beautiful Soup, then we're doing open parenthesis. We're gonna do two things. There's two parameters that we need to put in here. First, we need to put in this get request. So we actually need to name this and we'll call this page. We'll say page is equal to. And let's run this. And now we're going to put that page in here. And what we're going to say is .text. So the page is what's sending that request. And then the .text is what's retrieving the actual raw HTML that we're going to be using. Then we're going to put a comma here. And what we need to specify is how we're going to parse this information. Now this is an HTML. So what we're going to do is HTML just like this. This is standard that's already built into this library. So we don't need to go any further, but it's basically going to parse the information in an HTML format. Let's go.

ahead and run this. Let's see what we get. And as you can see, we have a lot of information. And as we scroll down, I'll try to point out some things that we've already looked at in previous lessons. Um, something like this th tag, that should be very similar, that's the title. Then we have these TD tags. And then of course, if we scroll down even further, we'll have things like ATR tag. So these are all things that we looked at in that first lesson when learning about HTML. Now again, we want to assign this to a variable. So we're going to say soup, that's going to say equal to this information right here. Now I'm not going to go into all the history behind Beautiful Soup. What I will say is the guy who created this Beautiful Soup Library, what he said was is that it takes this really messy HTML or XML, which you can also use it for, and it makes it into this kind of Beautiful Soup. So I just that was kind of funny, but that's why we're calling it soup.

right here, and we're gonna go ahead and run this, and we'll come right down here, and we'll say print soup. And let's run it, and now we have everything in here. So we have our HTML, our head, we have some href, and some links in here. And let's scroll down a little bit more, and then we have our body right there. And of course, we have a bunch of information in here. Now, in the next lesson, what we're going to be doing is learning how to kind of query all of this to take specific information out and basically understand a lot of what's going on in this HTML to make sure we can actually get what we need. Now, if this looks really kind of messy to you and it just doesn't make a lot of sense, there is one more thing that I'm going to show you, and we'll come right down here. So we'll say soup. Dot printify. And if you've ever used a different type of programming languages, protify is very common in a lot of them.

we'll just make it a little bit more easy to visualize and see. You'll notice that it kind of has this hierarchy built in, whereas if we scroll up, there's no hierarchy built in. It's all just down this left-hand side. So if you kind of want to view it and just kind of visually see the differences, this does help a lot, but it doesn't actually help a lot when you're, you know, querying it or using, you know, find and find all, which is what we're going to look at in the next lesson. So that is our lesson on Beautiful Soup and requests. In the next two lessons, we're going to be looking at find and find all, as well as really diving into things like variable strings and tags and classes and all those things. And then in the last lesson, we're going to do kind of this mini project where we try to get all the data from this webpage that we've been using from that table and put it into a Pandas data frame. So thank you guys so much for

watching, I really appreciate it. If you like this video, be sure to like and subscribe below, and I will see you in the next one. [Music] Thank you. [Music]

BeautifulSoup + Requests | Web Scraping in Python

Alex The Analyst

Introduction to Beautiful Soup and Requests in Python

Beautiful Soup and Requests are essential Python packages for web scraping, particularly for beginners.

These packages are used to extract HTML data from websites and make it usable for further manipulation.

The process involves importing the Beautiful Soup and requests modules, obtaining the HTML from a specific URL, and then navigating and extracting desired information using various HTML elements and attributes.

Using Python to Send a Get Request to a URL

The code assigns a URL to a variable and uses the requests library to send a get request to the URL, receiving a response object.

Different response codes such as 200, 204, 400, or 404 indicate the success or failure of the request.

The HTML from the website is then retrieved, providing a snapshot of the web page's content at that time.

The Beautiful Soup package is used to make a get request and retrieve raw HTML data.

It is then employed to parse the HTML information, allowing for easy navigation of tags and elements.

Beautiful Soup was created to handle messy HTML and XML, making the data more accessible for scraping.

Learning to Query HTML with Beautiful Soup

The tutorial covers how to navigate and understand HTML structure using Beautiful Soup.

The next lessons will focus on using find and find all, working with variable strings, tags, and classes.

The final lesson will involve a project to extract data from a webpage and create a Pandas data frame.

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Building a loyal subscriber base can significantly impact the channel's growth and success.

Expressing gratitude to the audience for their support helps to strengthen the creator-viewer relationship.