Semalt – Super Guide On How To Extract Amazon Product Details Using Python

Scraping large sets of data from websites such as Amazon is not that easy. The sites can only allow you to access 400 web pages per category. Amazon and other large e-commerce websites use ASIN, a keyword utilized by e-commerce websites to track down the number of products in a database.

In this post, you will learn how to create a product scraper that will be later used to extract product descriptions and pricing details on Amazon. For beginners, Python is a purpose-oriented programming language that emphasizes on script readability. Here are ways on how to use your product scraper.

Monitoring products on Amazon

Web scraping is widely used in extracting large sets of data from e-commerce websites. With a product scraper, you can easily track down the availability of stock, customer ratings, and changes in prices.

Analyzing how products are selling on Amazon

Web data extraction entails extracting useful data from sites. To survive stiff competition in the financial markets, you have to track down your competitors' performance. For the past few years, scraping sites from e-commerce sites has been a tedious and cumbersome activity. Thanks to Python, scraping these sites has been made easy.

A product scraper easily scrapes data from Amazon by highlighting their ASIN. Extracted data is used by financial marketers to analyze how commodities are selling on Amazon. Scrapers are used for various purposes. Here are other uses of product scrapers.

  • Analyzing Amazon's product ratings and reviews
  • Examining commodities advertising API
  • Analyzing rate parity and transparency

Why Python?

Python is highly recommended when it comes to extracting and parsing files from dynamic websites such as Amazon. However, before digging more in-depth on how to retrieve data from e-commerce websites, let's consider details that can be extracted from these sites. Here is a pin-pointed list that highlights sets of data that can be obtained with a product scraper.

  • Product's sale price
  • Stock availability
  • Product's category
  • Product's name
  • The original price

Python's package requirements

In this post, the central theme is using Python to download and parse HTML. Retrieving your data using Python is like right-clicking an element. It's that simple. Download HTML from your preferred product's web page and identify all XPath of the targeted component such as price and product's description.

The Python code

Do you have the name of the code to use? If yes, let's get going. Simply type-out your code's name on your command prompt. After getting the code, modify it with your own ASINs. A JSON output file (data.json) comprising of all the lists of ASINs data will be created.

Policies and terms govern e-commerce websites. When scraping, avoid violating the website's plans to avoid blacklisting. E-commerce websites limit users from accessing more than 400 pages per category. With Python's product scraper, you can easily monitor products for rating and stock accountability.