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Community-Driven Local Shopping Platform

Introduction

This project aims to revolutionize local shopping by providing real-time inventory updates, price comparisons, and community-driven reviews. Our platform bridges the gap between traditional shopping and modern e-commerce by making local commerce more transparent, accessible, and efficient.

Features

  • Real-Time Inventory Updates: Instantly check stock availability at nearby stores.
  • Price Comparison Tool: Compare prices across local stores to find the best deals.
  • Store Ratings & Reviews: Community-driven insights on store quality and reliability.
  • User-Friendly Interface: A simple and intuitive interface built with React.js.
  • Scalability & Performance: Uses cloud hosting for efficient performance.

Tech Stack

Frontend:

  • React.js for responsive UI development.

Backend:

  • Node.js and Express.js for API development.
  • PostgreSQL for structured data management.
  • Socket.IO for real-time inventory updates.

Cloud Hosting:

  • AWS or Google Cloud for scalability and reliability.

Database Schema

Tables:

  1. Users - Stores user information.
  2. Stores - Stores retailer information.
  3. Products - Stores product details.
  4. Inventory - Tracks product availability at stores.
  5. Reviews - Contains user-generated ratings and feedback.
  6. PriceComparison - Stores real-time price comparisons for products.

Installation & Setup

Prerequisites:

  • Node.js and npm installed
  • PostgreSQL installed

Steps:

  1. Clone the Repository

    git clone https://github.com/your-repo/digitalocalshop.git
    cd digitalocalshop
  2. Install Dependencies

    npm install
  3. Set Up Database

    • Create a PostgreSQL database.
    • Run the SQL scripts to set up tables.
  4. Start the Backend Server

    node server.js
  5. Start the Frontend

    cd client
    npm start

API Endpoints

  • GET /stores - Fetch all stores.
  • GET /products/:store_id - Get products for a store.
  • POST /review - Add a review.
  • PUT /inventory/update - Update inventory in real-time.

Future Enhancements

  • Implement AI-driven demand forecasting.
  • Introduce personalized recommendations for users.
  • Expand to mobile apps using React Native.

Contributors

  • Nilancy Agarwal
  • Priyam Prasad Sahoo
  • Kangkana Barman
  • Agnik Dutta

License

This project is licensed under the MIT License.

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