Fashion E-Commerce Store
When I started this project, the brief was simple to state and deceptively large to build: a full fashion e-commerce platform — product catalog, size and color variants, filters, an "AI-style" size recommender, cart, checkout, JWT auth, order tracking, and a wishlist. Here's a walkthrough of how it came together, the decisions behind the architecture, and a few lessons learned along the way. Why…
This fashion e-commerce platform project began with the goal of building a comprehensive online store with product catalog, size and color variants, filters, AI-style size recommender, cart, checkout, JWT auth, order tracking, and wishlist. FastAPI and MySQL were chosen for the backend, while Bootstrap 5 and vanilla JavaScript were used for the frontend.
The product catalog required an efficient model to handle multiple sizes and colors, which was achieved by creating a separate ProductVariant table linked to the Product table. The AI-based size recommendation engine was built as a rule-based system, utilizing size charts for easy implementation and future replacement with machine learning models.
Checkout was designed with a PaymentGateway interface to allow for easy integration of real payment providers later on. The checkout flow also included a mechanism to handle potential race conditions where multiple users might attempt to purchase the last item in stock simultaneously. Bcrypt was initially used for password hashing, but a compatibility issue arose during testing, which was resolved by calling bcrypt directly instead of through passlib.
The project also learned about the importance of thorough testing and catching potential issues before moving to production. Future improvements could include rate limiting, switching to real object storage for product images, and integrating a real payment gateway.
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