Data Scraping for an E-commerce Website

Data Scraper

Data Engineer

BeautifulSoup

Python

Selenium

Asif is one of the best Python developers I have worked with till date. He went above and beyond to deliver the work and accommodated all my requests. You will not go wrong with Asif, he is a capable developer and a thorough professional.

Client's Objective

The client needed a Python script to scrape product data from a website based on a specified subcategory. The script had to:

Accept a subcategory input.

Retrieve the subcategory page's response.

Iterate through the products on the subcategory page.

Visit each product page and extract the following details:

Solution Provided

The client requested a flexible script that could be easily modified to configure a URL and scrape product details, saving the results in a CSV file. The delivered solution included:

A command-line interface for inputting the category and optional subcategory names, eliminating the need for hardcoded URLs.

Implementation of multiprocessing to enable rapid data scraping, significantly reducing processing time.

Comprehensive documentation for debugging, maintenance, and installation support.

Proper encoding handling for Arabic text to avoid any parsing issues.

Data Retrieval Process

The script requires the user to input the subcategory name. It then constructs the complete URL based on the provided subcategory and requests the product page's response. The script iterates through each product, visiting individual product pages to extract the required information.

Output

The final data is parsed, cleaned, checked for encoding issues, and saved as a CSV file for further analysis.

This solution not only met the client's requirements but also provided a scalable and efficient approach to web scraping, ensuring data integrity and ease of use.