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Abstract (22cos237)

This project aims to automate the process of comparing product prices across various e-commerce websites using Python. It utilizes web scraping libraries like Beautiful Soup and Selenium to extract price data from platforms such as Amazon and eBay, presenting it in a user-friendly format for easy comparison. Future enhancements may include currency conversion and price drop alerts, ultimately facilitating smarter online shopping for consumers.

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laksharavi02
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31 views2 pages

Abstract (22cos237)

This project aims to automate the process of comparing product prices across various e-commerce websites using Python. It utilizes web scraping libraries like Beautiful Soup and Selenium to extract price data from platforms such as Amazon and eBay, presenting it in a user-friendly format for easy comparison. Future enhancements may include currency conversion and price drop alerts, ultimately facilitating smarter online shopping for consumers.

Uploaded by

laksharavi02
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
Available Formats
Download as DOCX, PDF, TXT or read online on Scribd
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E commerce price comparison website

Name: R.Parkavi Padma

Rollno: 22cos237

Abstract:

With the exponential growth of online shopping, consumers are often faced with the
challenge of navigating through various e-commerce websites to find the best deals on
products. The manual process of comparing prices across multiple platforms can be time-
consuming and inefficient. This project aims to address this problem by automating the
process of comparing the price of a product from multiple e-commerce websites using
Python, making it easier for consumers to make informed purchasing decisions. The core
objective of this project is to create a tool that scrapes product price data from popular e-
commerce platforms such as Amazon, eBay, Walmart, and Flipkart. Using Python’s web
scraping libraries, including Beautiful Soup and Requests, the program extracts the price
information directly from the HTML of the product pages. In cases where websites employ
JavaScript to load content dynamically, Selenium is used to simulate browser interactions and
capture the price details accurately. Once the prices are scraped, they are displayed in a user-
friendly format for easy comparison. The program handles price formatting issues such as
removing currency symbols and ensuring consistent units for comparison. Additionally, the
system can store and process the data in a structured format using Pandas, enabling users to
view the prices in a table and determine the most cost-effective option. This project not only
allows users to compare prices across different websites, but also has the potential for future
enhancements. For example, incorporating currency conversion APIs can enable comparisons
for international prices, while setting up price drop alerts can notify users when a product’s
price decreases. In conclusion, this Python-based price comparison tool provides an efficient
solution for consumers, saving both time and effort in finding the best deals across multiple
e-commerce platforms, ultimately promoting smarter online shopping.

System Requirements:

Front-end: Html, CSS

Back-end: Python

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