A Guide to Scraping Dynamic e-Commerce website with Python

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Dynamic Website — An Introduction

Today, businesses increasingly make data-driven decisions with the growth in online data volume. Here, websites play a crucial role as they are the cornerstone of online businesses. As such, these websites must be sturdy and interactive enough to scale up a company’s stature. The type of website chosen determines the effectiveness of the business. For all this, e-commerce web scraping becomes crucial.

In most cases, Dynamic websites get used more in the present moment than static ones, another type of website known and used by some industries.

But what exactly do we mean by Dynamic websites? What are their benefits, and how can they get scraped using Python?

Well, let us answer all these WHYs!

Dynamic websites are those that are changeable. These websites use server scripting or client-side to prepare dynamic content and possess HTML information. Such websites change the content with each request sent to the web server and can make different content for various visitors with the help of the same source code file.

Two kinds of dynamic web pages exist- client-side scripting and server-side scripting. The client-side pages changes per one’s web page activity. On the other hand, on server-side pages, the pages get changed whenever a web page gets loaded.

Whenever a browser loads such a page, the database receives a request to give information per user input. After receiving information, the resulting web page is applied to the user after styling codes are used. Different languages get used to making dynamic web pages like ASP, PHP, .NET, and JSP.

A dynamic website has some prominent features that make them a much-sought-after option for users:

  • Dynamic websites are flexible in their entirety.
  • The content of these websites changes quickly on the user’s computer without having to make a new page request to the browser.
  • In Dynamic websites, the owner can update and add new content to the page.
  • These websites have a featured content management system, e-commerce system, and intranet or extranet facilities.
  • Most dynamic web content becomes assembled on the web using server-scripting languages.

Dynamic websites get used in various applications ranging from forums, online booking systems, E-commerce sites, voting or polls, and e-newsletters.

Benefits of Dynamic Websites

Following Are The Myths And Legality Encircling Web Extraction And Its Uses:

Some important benefits of Dynamic websites are as follows:-

Easy to Update

In dynamic websites, a change in the page’s content leads to changes in other pages too, without interfering with the look. Due to this, dynamic websites become updated quickly and easily.

Scalability also becomes convenient with dynamic websites because they offer quicker and easier handling of innumerable pages. The page has an in-built flexibility to get developed as and when required.

Enhanced User-Experience

A dynamic website is user-friendly intrinsically. It enables end-users to make website changes conveniently per their requirements. They are interactive, allowing visitors to leave a reply or send

comments based on their experience while using the website. All this aids the creator in knowing about real-time reviews that they can work upon and improve. Building a navigational pathway, adding or

improving functionalities, responding to the user’s browsing experience, etc., can get done, thereby improvising the experience.

Easier Maintenance

Dynamic websites use a content management system that contains the element’s database and the page’s content. They run on scripting languages that interact with the information stored in the database.

The websites enable making side-wide changes without the requirement of making changes one by one. These websites also allows one to upload content and edit designs and backgrounds without much ado.

Innovative

Being interactive enables dynamic websites to have a futuristic approach. They allow users to be more engaged and involved with the content present on the web page. By lending a responsive and

interactive atmosphere, dynamic pages enhance the users browsing, making it more personalized. These experiences stay longer with the customers compared to static texts and images.

Professional Look

The looks of dynamic websites are professional. Static Websites are usually ideal for portraying the products on the website and allow users to call and book orders, which makes them look unprofessional. Hence, dynamic websites get preferred more.

Scraping Dynamic Website using Python

Python has always been considered a good option for web scraping. It consists of numerous libraries and frameworks that can help with data extraction. Easy to learn and with simple syntax in use, no wonder Python works as an efficient and faster method to scrape relevant information.

For Scraping Dynamic Websites with Python, follow these simple steps:

  • Use a headless web browser to scrape a dynamic website. The first step begins with the importing of required libraries. As such, use a mix of BeautifulSoup and Selenium to scrape the needed data.
  • To scrape the data, begin by getting familiar with the location of the data. The easiest way to locate an element is to open the Chrome dev tools and inspect the required information.
  • The next step is extracting the resultant page links. Now, scrape a website and collect the URLs of different pages of search results. Here a while loop gets used to iterate through the search result pages. The loop starts by navigating to the current URL using ‘driver. get()’ method. It then gets the page’s HTML source code using ‘driver.page_source’ and parses it. Store each of the page_url in the list page_lst_link.
  • Now scrape links of the product from the resultant pages. Here, the ‘page_lst_link’ variable must contain a list of page links. The code will iterate through each page link and use the web driver to navigate to that page. Use BeautifulSoup to parse the HTML of the page. Now, extract all product links. Store each of the product links in the list product_links.
  • Here, create a data frame to store the data that gets scraped. Form the data frame per the need. Scrape the needed information.
  • Store the requests from the URL in page_content with the help of the selenium web driver. Make the product_soup variable by parsing page_content with Beautifulsoup. Also, create the dom using ElementTree. This method returns the dom that gets used to extract chosen elements from the page using methods like.xpath() and .cssselect().
  • Once the relevant information gets extracted, create a CSV file. With this, you are done with scraping the Dynamic website.

Final Thoughts

Dynamic websites combined with web scraping have revolutionized how businesses work. They have helped enterprises make better and more informed decisions, have greater output, and make sales profit in a whole new way. By generating real-time information and working on it per the views, time zones, and other aspects, these websites have aided companies in making decisions that lead to better output in the long run.

In combination with Python, these websites work efficiently. Today, the programming language has turned into a powerful tool that offers innumerable libraries and frameworks to understand and handle different types of information. With the aid of web scraping and Python, various industries have witnessed phenomenal success over time. Indeed, dynamic websites, aided by web extraction have made data collection faster, boosting enterprises immensely.

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Data Scraping Services and Data Extraction
Data Scraping Services and Data Extraction

Written by Data Scraping Services and Data Extraction

3i Data Scraping is an Experienced Web Scraping Service Provider in the USA. We offering a Complete Range of Data Extraction from Websites and Online Outsource.