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How To Extract A Website As Well As Scraping HTML Code Using HTML Scraping?

Author: Webscreenscraping Web Data
by Webscreenscraping Web Data
Posted: Feb 18, 2022

Nearly every site online is written in HTML.

In case, you wish to automatically scrape data from any website, you might need to cope with a bundle of HTML codes.

A web data scraper can assist you scrape data from any website as well as pull any particular HTML attributes like title tags and class.

Use a Web Scraper to Do HTML Scraping

For instance, we would be utilizing Web Screen Scraping Scraper, a powerful data scraper.

One particular feature, which will assist us with the project, is Web Screen Scraping’s capability to pull the HTML codes and attributes from any website rather than only pulling the page text.

Also, we will extract the initial pages of Amazon results for a term called "smartphone".

Set up a Data Scraping Project

Initially, you need to download as well as install Web Screen Scraping Scraper. Once done, just click on a New Project as well as submit a URL we would be extracting.

Web Screen Scraping will render a page as well as you would be able to choose the data that you love to scrape.

Choose and Scrape Data
  1. Once submitting the URL, just scroll down towards the initial organic results on a page as well as click on title of an initial product given on a page. This would be highlighted in color green to suggest, this has been chosen.
  2. Rest of the products on a page would get highlighted in color Yellow. Then click on second result of a page to choose them (they would now get highlighted in color green).
  3. Web Screen Scraping is scraping the name as well as URL for every product on a page as these are available in the elements we have chosen.
  4. On left-hand sidebar, we could rename the product selection.

Now as we have chosen a few data to scrape, we can get extra data from an HTML code within the selection.

Scrape HTML Data

When you’ve chosen a few data to scrape, you can choose every extraction on left-hand sidebar. Here, we get two scrapings: one for product name as well as one for listing URL.

Now, you can choose the scrapings as well as use a dropdown for editing them and scraping particular HTML elements.

By default, the scraping would first scrape the text, which has been chosen.

Data Scraped: Text

Outcome: Samsung Galaxy A10 32GB (A105M) 6.2" HD+ with Infinity-V 4G LTE Factory Unlocked GSM Smartphone – Color Black

Now, we could also scrape the href Aspect for the selection (URL).

Data Scraped: URL (href Aspect)

Outcome: https://www.amazon.com/Samsung-A10-Infinity-V-Unlocked-Smartphone/dp/B07Q84DPZH/

The complete HTML extraction would scrape the whole HTML code from selection, it can be particularly helpful while selecting the whole DIVs on a page.

Data Scraped: Full HTML

Outcome: Samsung Galaxy A10 32GB (A105M) 6.2" HD+ Infinity-V 4G LTE Factory Unlocked GSM Smartphone - Black

The Inner HTML scraping will scrape any content available within HTML tags of a selection you’ve done.

Data Scraped: Inner HTML

Outcome: Samsung Galaxy A10 32GB (A105M) 6.2" HD+ with Infinity-V 4G LTE Factory Unlocked GSM Smartphone – Color Black

Attribute Scraping

In different cases, the selection would have many HTML attributes like class, title, or ID.

Web Screen Scraping data scraper will automatically recognize these attributes as well as permit you to scrape the data given within them.

Here, the selection we have done, Web Screen Scraping has chosen a class attribute. Now, we can select that from a dropdown to scrape the data explicitly.

Data Scraped: class Attribute

Outcome: a-color-base a-size-medium a-text-normal

Build and Run Your Scraper

What we have set today is an extremely easy scraping project because this is only scraping the names as well as URL for every product at one page.

By following this blog, you would be able to scrape data from a website as well as into the spreadsheet comprising HTML data as well as attributes.

For more information, contact Web Screen Scraping or ask for a free quote!

About the Author

Sam Morris, Writing article and blogs realted to data analystics and data extraction process.

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Author: Webscreenscraping Web Data

Webscreenscraping Web Data

Member since: Jul 26, 2021
Published articles: 71

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