Car Performance Database

A comprehensive web application for comparing car performance data across 60,000+ vehicles. Search, filter, and sort by acceleration times, top speeds, lap times, power output, and more.

Features

• 60,000+ Vehicles: Data aggregated from multiple authoritative sources
• Performance Metrics: 0-60 mph, quarter mile, top speed, Nurburgring lap times, and more
• Advanced Filtering: Filter by manufacturer, country, year range, and propulsion type
• Full-Text Search: Search across manufacturer and model names
• Server-Side Pagination: Fast loading with SQLite-backed API
• Dark Mode Support: Automatic theme detection
• Responsive Design: Works on desktop and mobile

Tech Stack

• Frontend: Next.js 16, React 19, TanStack Table v8
• Styling: Tailwind CSS 4
• Database: SQLite with better-sqlite3
• Validation: Zod
• ETL Pipeline: Python 3.11+

Data Sources

Source	Description	Priority
Car and Driver	Instrumented test data (0-60, quarter mile, skidpad)	High
Car and Driver Lightning Lap	VIR track lap times (2006-2025)	High
Wikipedia Nurburgring	Nordschleife lap times	Medium
Wikipedia Top Gear	Test track Power Lap times	Medium
Wikipedia Records	Acceleration and speed records	Medium
Autoevolution	Comprehensive vehicle specifications	Medium
EPA Fuel Economy	Official vehicle specifications	Low
Kaggle	Community-contributed specifications (1945-2020)	Low

Getting Started

Prerequisites

• Node.js 18+
• Python 3.11+ (for ETL pipeline)
• npm or yarn

Installation

# Install Node.js dependencies
npm install

# Install Python dependencies (for ETL)
pip install pyyaml beautifulsoup4

Development

# Start the development server
npm run dev

Open http://localhost:3000 to view the application.

Building for Production

# Build the Next.js application
npm run build

# Start the production server
npm start

Project Structure

car-performance-comparison/
├── src/
│   ├── app/                    # Next.js app router pages
│   │   ├── api/cars/           # API routes for car data
│   │   └── page.tsx            # Main application page
│   ├── components/             # React components
│   │   ├── DataTable.tsx       # Main data table with TanStack
│   │   ├── FilterPanel.tsx     # Filter controls
│   │   └── Pagination.tsx      # Pagination controls
│   ├── hooks/                  # Custom React hooks
│   │   └── useCarsApi.ts       # API data fetching hook
│   ├── lib/                    # Utilities
│   │   ├── db.ts               # SQLite database service
│   │   └── schemas.ts          # Zod validation schemas
│   └── types/                  # TypeScript types
│       └── car.ts              # Auto-generated car data types
├── etl/                        # Python ETL pipeline
│   ├── cli.py                  # CLI entry point
│   ├── config/
│   │   ├── schema.yaml         # Data field definitions
│   │   └── sources.yaml        # Data source configuration
│   ├── core/
│   │   ├── converters.py       # Value parsing/conversion
│   │   ├── enricher.py         # Data enrichment
│   │   ├── manufacturers.py    # Manufacturer normalization
│   │   ├── merger.py           # Multi-source data merging
│   │   └── schema.py           # Schema loading
│   ├── outputs/
│   │   ├── csv_writer.py       # CSV output
│   │   ├── sqlite_writer.py    # SQLite output
│   │   ├── typescript_gen.py   # TypeScript type generation
│   │   └── quality_report.py   # Data quality reporting
│   ├── parsers/                # Source-specific parsers
│   │   ├── base.py             # Base parser class
│   │   ├── caranddriver/       # Car and Driver parsers
│   │   ├── wikipedia/          # Wikipedia parsers
│   │   ├── fueleconomy/        # EPA data parser
│   │   ├── kaggle/             # Kaggle dataset parser
│   │   └── github/             # Autoevolution parser
│   └── validators/             # Data validation
└── public/data/                # Data files
    ├── car-performance-data.db # SQLite database
    └── car-performance-data.csv # CSV export

ETL Pipeline

The ETL pipeline aggregates data from multiple sources into a unified database.

Running the ETL

# Run full ETL pipeline
python -m etl.cli run

# Run with verbose output
python -m etl.cli run -v

# Generate only SQLite (skip CSV)
python -m etl.cli run --output-format sqlite

# Show pipeline status
python -m etl.cli status

Adding New Data Sources

1. Create a parser in etl/parsers/<source>/
2. Inherit from BaseParser in etl/parsers/base.py
3. Add source configuration to etl/config/sources.yaml
4. Register the parser in etl/parsers/registry.py

API Reference

GET /api/cars

Fetch paginated car data with optional filtering.

Query Parameters:

Parameter	Type	Default	Description
page	number	1	Page number
pageSize	number	50	Records per page (max 100)
sortBy	string	-	Column to sort by
sortOrder	asc/desc	asc	Sort direction
manufacturer	string	-	Filter by manufacturer
country	string	-	Filter by country code
yearMin	number	-	Minimum year
yearMax	number	-	Maximum year
search	string	-	Full-text search

Response:

{
  "data": [...],
  "pagination": {
    "page": 1,
    "pageSize": 50,
    "totalCount": 60997,
    "totalPages": 1220
  }
}

GET /api/cars/meta

Fetch filter metadata (manufacturers, countries, year range).

Response:

{
  "manufacturers": ["Acura", "Alfa Romeo", ...],
  "countries": [{"value": "US", "label": "United States"}, ...],
  "yearRange": {"min": 1886, "max": 2025},
  "totalCount": 60997,
  "sources": [{"value": "Car and Driver", ...}]
}

Performance Metrics

The database includes the following performance metrics:

Metric	Unit	Description
0-60 mph	seconds	Acceleration time
0-100 km/h	seconds	Acceleration time (metric)
0-100 mph	seconds	Acceleration time
Quarter Mile	seconds	1/4 mile time
Top Speed	mph/km/h	Maximum velocity
Nurburgring Lap	seconds	Nordschleife lap time
Top Gear Lap	seconds	TG test track time
Lightning Lap	seconds	VIR lap time
Power	hp/kW	Engine output
Torque	lb-ft/Nm	Torque output
Curb Weight	lbs/kg	Vehicle weight

License

Private project - not for distribution.