Today we are going to see how we can scrape Amazon reviews using Python and BeautifulSoup is a simple and elegant manner.

• Beautiful Soup Python
• Website Scraping With Python Using Beautifulsoup And Scrapy
• Web Scraping With Python And Beautiful Soup Pdf
• Web Scraping Python Bs4
• Web Scraping With Python Tutorial
• Web Scraping With Python Beautifulsoup Requests & Selenium Free Download

This article aims to get you started on a real-world problem solving while keeping it super simple, so you get familiar and get practical results as fas,t as possible.

So the first thing we need is to make sure we have Python 3 installed. If not, you can just get Python 3 and get it installed before you proceed.

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Beautiful Soup Python

Then you can install beautiful soup.

We will also need the library's requests, lxml, and soupsieve to fetch data, break it down to XML, and to use CSS selectors. Install them using.

Once installed, open an editor and type in.

Now let's go to amazon and inspect the data we can get. I have chosen a random USB charger page to scrape located here.

This is how it looks.

The reviews section looks like this.

Back to our code now. Let's try and get this data by pretending we are a browser like this.

Save this as amazon_bs.py.

If you run it.

You will see the whole HTML page.

Now, let's use CSS selectors to get to the data we want. To do that, let's go back to Chrome and open the inspect tool. You can see that all the review titles elements have a class called review-title in them.

Let's use CSS selectors to get this data like so. System requirements to download ms office 2008 for mac. Mac 2816 manualquotesdigital.

This will print the title of the first review. We now need to get to all reviews. We notice that the

To get to them individually, we run through them like this and try and get to the review title from 'inside' the 'review'

Website Scraping With Python Using Beautifulsoup And Scrapy

And when you run it, you get.

Web Scraping With Python And Beautiful Soup Pdf

Bingo!! We got the review titles.

Now with the same process, we get the class names of all the other data like review date, number of stars, reviewer name, and the review itself like this.

That, when run, should print everything we need from each review like this.

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