Web Scraping Tool for Amazon Product Data Extraction and Analysis
I developed a Python-based web scraping application to automatically extract detailed product listings and metadata from Amazon.in. The tool utilizes the Requests library to programmatically make HTTP requests to Amazon's website and Beautiful Soup for parsing the HTML content.
The scraper allows users to input search queries and specify the number of pages to scrape. It then dynamically retrieves a wide range of attributes for each result, including product name, URL, price, star rating, number of reviews, description, ASIN code, manufacturer details, and more. All extracted data is consolidated into a CSV file for downstream analysis and processing.
Some key capabilities include:
Flexible search criteria to target specific product categories or keywords
Pagination support to scrape multiple pages of results at once
Comprehensive data model with over 10 unique product attributes
CSV export for easy analysis in spreadsheet or database applications
This project demonstrates my skills in web scraping, data extraction, HTML/XML parsing, and scripting in Python. The tool has been helpful for market research, price monitoring, and product assortment analysis on Amazon.in. It provides a foundation for additional enhancements like data validation, storage in a database, or integration with business intelligence dashboards.
The code is open source and available on GitHub at https://github.com/dasdebanna/Amazon-Product-Scraper.