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Cozy Home

Welcome to Cozy Home, your one-stop destination for high-quality furniture online. Our platform offers a seamless shopping experience, allowing users to explore a wide range of furniture products, create accounts, manage carts, and much more.

cozy-home

Technologies Used

Frontend

React React  React router React router   TypeScript Typescript  Redux Redux  HTML HTML  Sass SCSS  
    
framer Framer-motion Swiper Swiper  Lenis scroll Lenis scroll  Formik.js Formik.js  LazyLoad Images

Hosted by Vercel Vercel

Backend

Java Java  kafka Kafka  Spring Boot Spring  mongoDB  MongoDB  Swagger  Swagger

Hosted by Render Vercel

Features

  • User Authentication: Secure user registration and login functionality.
    • Google Auth
    • Auth by emeil and confirmation list.
  • Shopping Cart: Users can add and remove products from their cart, also information saved on backend.
  • Favorites List: Create and manage a list of favorite products for quick access.
  • Product Filters: Extensive dynamic filters for easy product search based on categories, subcategories, color, size, height, weight, etc.
  • Product sliders for promo blocks: Slider sections showcasing popular products, new arrivals, similar products in categories.
  • Reviews: Users can view and add reviews for products.
  • Product Availability: Request products that are currently unavailable.
  • Lazy Loading: Optimized image loading for improved performance.
  • Password Recovery: Forgot your password? No problem! Users can reset their passwords securely.

Getting Started

To get started with Cozy Home, follow these steps:

  1. Clone the repository: git clone https://github.com/DmytryjK/teamchallange_web.git
  2. Install dependencies: npm install
  3. Start the development server: npm start

Make sure you have the backend server running as well to handle API requests.

Future Enhancements

  • Improved Filtering: Enhance the filtering options to provide more specific search results.
  • Advanced Analytics: Implement analytics tools to track user behavior and preferences.
  • Personalized Recommendations: Utilize machine learning algorithms to provide personalized product recommendations.
  • Social Media Integration: Enable users to share their favorite products on social media platforms.
  • Order Tracking: Introduce order tracking functionality to keep users informed about their purchases.

Task Management

  • Task Manager: Jira
  • Project Management: Mirro

License

This project is licensed under the MIT License.