Car Dealership Network - Full Stack Application

A full-stack car dealership platform built with Django, React, Node.js, and MongoDB featuring dealership discovery, customer reviews, and AI-powered sentiment analysis.

Project Overview

Full-stack microservices application that enables users to explore car dealerships, read and post reviews, and discover vehicle inventory across different locations. Features Django REST API, React frontend, Node.js microservice, and AI-powered sentiment analysis.

Key Technologies: Django | React | Node.js | MongoDB | NLTK | Docker

Features

Core Functionality:

• Dealership Directory - 50+ dealerships across multiple states with location-based search
• Vehicle Inventory - Car catalog with make/model management and search filters
• Review System - Customer reviews with AI sentiment analysis (NLTK/VADER)
• User Management - Registration, authentication, and profile management
• Responsive Design - Mobile-optimized interface with Bootstrap styling

Live Application Demo

Main landing page with dealership directory access

Application Screenshots

Company Information

About us page showcasing company leadership and mission

Contact information and customer service details

Dealership Search & Filtering

Filter dealerships by state with comprehensive dealer information

Review System with Sentiment Analysis

Customer review submission with car details and purchase information

AI-powered sentiment analysis displaying positive, negative, and neutral review classifications

Quick Start

Prerequisites: Python 3.9+, Node.js 18+, MongoDB 7.0+

# Clone repository
git clone https://github.com/RitaJind/xrwvm-fullstack_developer_capstone.git
cd xrwvm-fullstack_developer_capstone

# Start services (in separate terminals)
# Django backend
cd server && pip install -r requirements.txt && python manage.py runserver

# Node.js database service  
cd server/database && npm install && docker-compose up -d && node app.js

# Sentiment analysis
cd server/djangoapp/microservices && pip install -r requirements.txt && python app.py

# React frontend
cd server/frontend && npm install && npm start

Endpoints: Frontend: http://localhost:3000 | Backend: http://localhost:8000 | Database: http://localhost:3001

Application Flow

User Journey: Homepage → Dealership Listings → Dealer Details → Vehicle Inventory → Review System → User Account

Admin Features: Dealership Management, Inventory Control, Review Moderation, User Management, Analytics Dashboard

Architecture

Microservices: React SPA ↔ Django API ↔ Node.js API ↔ MongoDB + Sentiment Analysis Service (Flask/NLTK)

Tech Stack: Django 5.0+ | React 18+ | Node.js 18+ | MongoDB 7.0+ | Python 3.9+ | Docker

API Documentation

Key Endpoints:

• GET /djangoapp/get_dealers/ - Fetch all dealerships
• GET /djangoapp/get_dealers/{state}/ - Fetch dealerships by state
• POST /djangoapp/add_review/ - Submit a new review
• POST /djangoapp/login/ - User authentication
• GET /dealerships - Node.js: Get all dealerships
• POST /reviews - Node.js: Add new review
• POST /analyze/{text} - Sentiment analysis

Testing

# Backend testing
cd server && python manage.py test djangoapp

# Frontend testing  
cd server/frontend && npm test

# API testing
curl -X GET http://localhost:8000/djangoapp/get_dealers/

About the Developer

Rita Jindal - Software Engieer

Passionate about building scalable, secure, and maintainable software solutions. Experienced in microservices architecture, cloud-native, and full-stack software development.