ScentbaseX — Perfume Discovery & Comparison Platform

Overview

ScentbaseX is a perfume discovery and comparison platform developed with Python and Django to make fragrance information easier to explore and compare.

The platform was designed to help users discover perfumes and compare different fragrances using information organized within a centralized database. A key part of the project was building and populating a large perfume database through automated web scraping, reducing the need to collect and enter fragrance information manually.

The development involved creating a custom Django backend to manage fragrance data and support the platform's discovery and comparison functionality. Data collection and processing were important parts of the project, requiring an approach to gathering, organizing, and importing large volumes of perfume information into the database.

The project demonstrates practical experience in full-stack web development, database management, data scraping, and the development of data-driven web applications.

The problem

Finding and comparing perfumes can be challenging when fragrance information is scattered across different websites and databases. Users need a convenient way to explore fragrances, understand their scent profiles, and compare multiple perfumes without manually searching through numerous individual product pages.

ScentbaseX was developed to address this challenge by bringing perfume information into a centralized platform with dedicated discovery and comparison functionality. Another major challenge was sourcing and organizing a large volume of fragrance data to make the platform useful.

The solution

Developed ScentbaseX using Python and Django, creating a data-driven web application that enables users to discover fragrances and compare up to four perfumes side by side. The comparison functionality allows users to examine fragrance notes, accords, ratings, and scent profiles. scentbasex.com

A significant part of the project involved automated web scraping and large-scale database population. Developed a data collection and import workflow to gather perfume information, organize the records, and populate the database, reducing reliance on manual data entry.

The project combined backend development, database management, data processing, and user-facing comparison features to create a centralized fragrance discovery experience.