Manheim Deals Finder

A full-stack webapp to find the best car deals from Manheim auctions and other sources.

Project Structure

manheim-deals-finder/
��� app.jsx                    # React frontend (standalone with sample data)
��� ManheimDealsFinder.jsx     # Alternative React component
��� index.html                 # HTML shell with dark theme CSS
��� backend/
�   ��� main.py               # FastAPI server with all API endpoints
�   ��� config.py             # Configuration (DB, ports, intervals)
�   ��� models.py             # SQLAlchemy models + Pydantic schemas
�   ��� requirements.txt      # Python dependencies
�   ��� .env.example          # Environment variables template
�   ��� scrapers/
�       ��� __init__.py
�       ��� base_scraper.py   # Abstract base scraper class
�       ��� manheim_scraper.py # Manheim.com scraper (requires login)
�       ��� copart_scraper.py  # Copart auction scraper
�       ��� carscom_scraper.py # Cars.com scraper

Quick Start

Frontend Only (Preview with Sample Data)

Open app.jsx in any React environment or use the standalone index.html.

Full Stack Setup

1. Install Python dependencies:

cd backend
pip install -r requirements.txt

2. Copy and configure environment:

cp .env.example .env
# Edit .env with your Manheim credentials

3. Start the backend:

python main.py

The API runs at http://localhost:8000 with auto-docs at /docs.

Features

• Search & filter by make, model, year, price, mileage, fuel type, transmission
• Deal Score algorithm (compares price vs MMR value + condition + mileage)
• Side-by-side vehicle comparison (up to 3 cars)
• Price distribution & top makes charts
• Dark/Light mode toggle
• DealShield & Buy Now filters
• Pagination with smart page navigation

API Endpoints

Method	Endpoint	Description
GET	/api/cars	Search cars with filters
GET	/api/cars/{id}	Get car details
GET	/api/dashboard	Dashboard statistics
GET	/api/filters	Available filter options
POST	/api/scrape/{source}	Trigger manual scrape
POST	/api/alerts	Create price alert

Tech Stack

• Backend: Python, FastAPI, SQLAlchemy, APScheduler
• Frontend: React, Recharts, Lucide Icons
• Database: SQLite (default) / PostgreSQL
• Scrapers: Playwright/aiohttp-based