Intro To Web Scraping

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Our Beginner's Guide to Web Scraping

The internet has become such a powerful tool because there is so much information on there. Many marketers, web developers, investors and data scientists use web scraping to collect online data to help them make valuable decisions.

Aug 23, 2019 What is Web Scraping Web scraping, web harvesting or web data extraction is the process of extracting data from websites. To do this in Python, while there is multiple ways to achieve this (requests + beautiful soup, selenium, etc), my personal favourite package to use is Scrapy. Nov 17, 2020 Our Beginner's Guide to Web Scraping. The internet has become such a powerful tool because there is so much information on there. Many marketers, web developers, investors and data scientists use web scraping to collect online data to help them make valuable decisions.

Introduction to Web Scraping Internet is an ocean of information spread accross various websites, where it is categorized, interlinked and mostly freely available for everyone. Web Scraping is the automation of the data extraction process from websites. This event is done with the help of web scraping software known as web scrapers. They automatically load and extract data from the websites based on user requirements. These can be custom built to work for one site or can be configured to work with any website.

But if you’re not sure how to use a web scraper tool, it can be intermediating and discouraging. The goal of this beginner's guide is to help introduce web scraping to people who are new to it or for those who don't know where to exactly start.

We’ll even go through an example together to give a basic understanding of it. So I recommended downloading our free web scraping tool so you can follow along.

So, let’s get into it.

Introduction to Web scraping

First, it's important to discuss what is web scraping and what you can do with it. Whether this is your first time hearing about web scraping, or you have but have no idea what it is, this beginner's guide will help guide you to discover what Web scraping is capable of doing!

What is Web Scraping?

Web scraping or also known as web harvesting is a powerful tool that can help you collect data online and transfer the information in either an excel, CSV or JSON file to help you better understand the information you’ve gathered.

Although web scraping can be done manually, this can be a long and tedious process. That’s why using data extraction tools are preferred when scraping online data as they can be more accurate and more efficient.

Web scraping is incredibly common and can be used to create APIs out of almost any website.

How do web scrapers work?

Automatic web scraping can be simple but also complex at the same time. But once you understand and get the hang of it, it’ll become a lot easier to understand. Just like anything in life, you need practice to make it perfect. At first, you’re not going to understand it but the more you do it, the more you’ll get the hang of it.

The web scraper will be given one or more URLs to load before scraping. The scraper then loads the entire HTML code for the page in question. More advanced scrapers will render the entire website, including CSS and JavaScript elements.

Then the scraper will either extract all the data on the page or specific data selected by the user before the project is run.

Ideally, you want to go through the process of selecting which data you want to collect from the page. This can be texts, images, prices, ratings, ASIN, addresses, URLs etc.

Once you have everything you want to extract selected, you can then place it on an excel/CSV file for you to analyze all of the data. Some advanced web scrapers can convert the data into a JSON file which can be used as an API.

If you want to learn more, you can read our guide on What is Web Scraping and what it’s used for

Is Web Scraping Legal?

With you being able to attract public information off of competitors or other websites, is web scraping legal?

Any publicly available data that can be accessed by everyone on the internet can be legally extracted.

The data has to follow these 3 criteria for it to be legally extracted:

User has made the data public
No account required for access
Not blocked by robots.txt file

As long as it follows these 3 rules, it's legal!

You can learn more about the rules of web scraping here: Is web scraping legal?

Web scraping for beginners

Now that we understand what web scraping is and how it works. Let’s use it in action to get the hang of it!

For this example, we are going to extract all of the blog posts ParseHub has created, how long they take to read, who wrote them and URLs. Not sure what you will use with this information, but we just want to show you what you can do with web scraping and how easy it can be!

First, download our free web scraping tool.

You’ll need to set up ParseHub on your desktop so here’s the guide to help you: Downloading and getting started.

Once ParesHub is ready, we can now begin scraping data.

If it’s your first time using ParseHub, we recommend following the tutorial just to give you an idea of how it works.

But let’s scrape an actual website like our Blog.

For this example, we want to extract all of the blogs we have written, the URL of the blog, who wrote the blog, and how long it takes to read.

Your first web scraping project

1. Open up ParseHub and create a new project by selecting “New Project”

2. Copy this URL: https://www.parsehub.com/blog/ and place it in the text box on the left-hand side and then click on the “Start project on this URL” button.

3. Once the page is loaded on ParseHub there will be 3 sections:

Command Section
The wbe page you're extracting from
Preview of what the data will look like

The command section is where you will tell the software what you want to do, whether this is a click making a selection, or the advanced features ParseHub can do.

4. To begin extracting data, you will need to click on what exactly you want to extract, in this case, the blog title. Click on the first blog title you see.

Once clicked, the selection you made will turn green. ParseHub will then make suggestions of what it thinks you want to extract.

The suggested data will be in a yellow container. Click on a title that is in a yellow container then all blog titles will be selected. Scroll down a bit to make sure there is no blog title missing.

Now that you have some data, you can see a preview of what it will look like when it's exported.

5. Let’s rename our selection to something that will help us keep our data organized. To do this, just double click on the selection, the name will be highlighted and you can now rename it. In this case, we are going to name it “blog_name”.

Quick note, whenever renaming your selections or data to have no spaces i.e. Blog names won't work but blog_names will.

Now that all blog titles are selected, we also want to extract who wrote them, and how long they take to read. We will need to make a relative selection.

6. On the left sidebar, click the PLUS (+) sign next to the blog name selection and choose the Relative Select command.

7. Using the Relative Select command, click on the first blog name and then the author. You will see an arrow connect the two selections. You should see something like this:

Let’s rename the relative selection to blog_author

Since we don’t need the image URL let’s get rid of it. To do this you want to click on the expand button on the “relative blog_author” selection.

Now select the trash can beside “extract blog_author”

8. Repeat steps 6 and 7 to get the length of the blog, you won't need to delete the URL since we are extracting a text. Let's name this selection “blog_length”

It should look like this.

Since our blog is a scrolling page (scroll to load more) we will need to tell the software to scroll to get all the content.

Web Scraping Free

If you were to run the project now you would only get the first few blogs extracted.

9. To do this, click on the PLUS + sign beside the page selection and click select. You will need to select the main element to this, in this case, it will look like this.

10. Once you have the main Div clicked you can add the scroll function, to do this On the left sidebar, click the PLUS (+) sign next to the main selection, click on advanced, then select the scroll function.

You will need to tell how long the software to scroll, depending on how big the blog is you may need a bigger number. But for now, let’s put it 5 times and make sure it's aligned to the bottom.

If you still need help with the scroll option you can click here to learn more.

We will need to move the main scroll option above blog names, it should look like this now:

11. Now that we have everything we want to be extracted; we can now let ParseHub do its magic. Click on the “Get data” button

12. You’ll be taken to this page.

You can test your extraction to make sure it’s working properly. For bigger projects, we recommend doing a test run first. But for this project let's press “run” so ParseHub can extract the online data.

13. This project shouldn’t take too long, but once ParseHub is done extracting the data, you can now download it and export it into a CSV/Excel, JSON, or API. But we just need a CSV/ Excel file for this project.

And there you have it! You’ve completed your first web scraping project. Pretty simple huh? But ParseHub can do so much more!

What else can you do with web scraping?

Now that we scraped our blog and movie titles (if you did the tutorial), you can try to implement web scraping in more of a business-related setting. Our mission is to help you make better decisions and to make better decisions you need data.

ParseHub can help you make valuable decisions by doing efficient competitor research, brand monitoring and management, lead generation, finding investment opportunities and many more!

Whatever you choose to do with web scraping, ParseHub can Help!

Check out our other blog posts on how you can use ParseHub to help grow your business. We’ve split our blog posts into different categories depending on what kind of information you're trying to extract and the purpose of your scraping.

Ecommerce website/ Competitor Analysis / Brand reputation

Lead Generation

Brand Monitoring and Investing Opportunities

Closing Thoughts

There are many ways web scraping can help with your business and every day many businesses are finding creative ways to use ParseHub to grow their business! Web scraping is a great way to collect the data you need, but can be a bit intimidating at first if you don’t know what you’re doing. That’s why we wanted to create this beginner's guide to web scraping to help you gain a better understanding of what it is, how it works, and how you can use web scraping for your business!

If you have any trouble with anything, you can visit our help center or blog to help you to navigate with ParseHub or can contact support for any inquiries.

Learn more about web scraping

Intro To Web Scraping Using

If you want to learn more about web scraping and elevate your skills, you can check out our free web scraping course! Once completed, you'll get a certification to show off your new skills and knowledge.

Happy Scraping!

What is web scraping

This is the process of extracting information from a webpage by taking advantage of patterns in the web page's underlying code.We can use web scraping to gather unstructured data from the internet, process it and store it in a structured format.In this walkthrough, we'll be storing our data in a JSON file.

Alternatives to web scraping

Though web scraping is a useful tool in extracting data from a website,it's not the only means to achieve this task.Before starting to web scrape, find out if the page you seek to extract data from provides an API.

robots.txt file

Ensure that you check the robots.txt file of a website before making your scrapper. This file tells if the website allows scraping or if they do not.To check for the file, simply type the base URL followed by '/robots.txt'An example is, 'mysite.com/robots.txt'.For more about robots.txt files this post should provide better incite.

Getting started

In this tutorial, we'll be extracting data from books to scrape which you can use to practise your web scraping.We'll extract the title, rating, link to more information about the book and the cover image of the book.

Find the code on github.

1. Importing libraries

The python libraries perform the following tasks.

requests - will be used to make Http requests to the webpage.
json - we'll use this to store the extracted information to a JSON file.
BeautifulSoup - for parsing HTML.

2. walkthrough

We're initializing three variables here.

header-HTTP headers provide additional parameters to HTTP transactions. By sending the appropriate HTTP headers, one can access the response data in a different format.
base_url - is the webpage we want to scrape since we'll be needing the URL quite often, it's good to have a single initialization and reuse this variable going forward.
r - this is the response object returned by the get method. Here, we pass the base_url and header as parameters.

To ensure our scraper runs when the http response is ok we'll use the if statement as a check. The number 200 is the status code for Ok. To get a list of all codes and their meanings check out this resource.We'll then parse the response object using the BeautifulSoup method and store the new object to a variable called soup.

From the aforementioned definition,

Web scraping the process of extracting information from a webpage by taking advantage of patterns in the web page's underlying code.

Let's take a look at a single record from our webpage to identify the patterns. Once we can see the page, we'll loop through every record in the page as they contain similar traits.From the image above, we'll notice that all books are contained within a list item with the class col-xs-6 col-sm-4 col-md-3 col-lg-3By using the find_all() method, we can find all references of this HTML tag in the webpage. we pass the tag as the first argument and then using the attrs argument which takes in a python dictionary, we can specify attributes of the HTML tag selected. In this case, it was a class indicated above, but you can even use id as an attribute.

Store the result in a variable, I chose the name books.

If we observe keenly, we'll notice that each of the elements we want to extract is nested within the list item tag are all contained in similar tags, in the example above. The title of the book is between h3 tags.The find() method returns the first matching tag.text will simply return any text found within the tags specified.For the anchor tags, we'll be extracting the hyper reference link.As opposed to h3 tag, the href element is within anchor tags in HTML. Like so<a href='somelink.com'></a>In this case, the returned object will behave like a dictionary where we have a dictionary_name[key]

We do this iteratively for all the values we seek to extract because we are taking advantage of the pattern in the underlying code of the webpage. Hence the use of the python for loop.

The extracted elements are then stored in respective variables which we'll put in a dictionary. With this information, we can then comfortably append the dictionary object to the initialized result list set before our for loop.

Intro To Web Scraping Pdf

Finally, store the python list in a JSON file by the name 'books.json' with an indent of 4 for readability purposes.

With that, you have your simple web scraper up and running. For more on web scrapers, read the documentation for the libraries or on youtube.

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