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Autoparts-DB/vehicle_database/GETTING_STARTED.md
consultoria-as f395d67136 Initial commit: Sistema Autoparts DB
- Base de datos SQLite con información de vehículos
- Dashboard web con Flask y Bootstrap
- Scripts de web scraping para RockAuto
- Interfaz CLI para consultas
- Documentación completa del proyecto

Incluye:
- 12 marcas de vehículos
- 10,923 modelos
- 10,919 especificaciones de motores
- 12,075 combinaciones modelo-año-motor
2026-01-19 08:45:03 +00:00

2.6 KiB

Vehicle Database - Getting Started Guide

Overview

This project provides a comprehensive database system for storing information about vehicle brands, models, years, and engines. The database is built using SQLite and managed through Python scripts.

Database Structure

The database consists of five main tables:

  • brands: Vehicle manufacturers (Toyota, Ford, etc.)
  • models: Vehicle models (Camry, F-150, etc.)
  • engines: Engine specifications (2JZ-GTE, EcoBoost, etc.)
  • years: Calendar years for vehicle production
  • model_year_engine: Junction table linking all entities with trim levels and specifications

Setup and Usage

1. Initial Setup

Run the setup script to initialize the database:

cd vehicle_database
./setup.sh

2. Querying the Database

Use the interactive query interface:

python3 scripts/query_interface.py

The query interface allows you to:

  • Search for vehicles by brand, model, year, or engine
  • Browse all available brands
  • View models for specific brands
  • See production years for specific models

3. Managing the Database

Use the database manager for programmatic access:

python3 scripts/database_manager.py

4. Importing Data

To import data from CSV files:

  1. Prepare your data in the required CSV format
  2. Use the CSV importer functionality in your own scripts

Sample CSV files are provided in the data/ directory.

Example Queries

The system supports various search options:

  • Find all vehicles by a specific brand
  • Search for a specific model across all years
  • Filter by engine type or specifications
  • Look up trim levels and drivetrain configurations

Extending the Database

To add more data:

  1. Use the Python API in scripts/database_manager.py
  2. Directly execute SQL commands on the SQLite database
  3. Import data from CSV files using the structure provided

File Structure

vehicle_database/
├── sql/
│   └── schema.sql          # Database schema
├── scripts/
│   ├── database_manager.py # Main database manager
│   ├── query_interface.py  # Interactive query interface
│   └── csv_importer.py     # CSV import functionality
├── data/                   # Sample CSV data files
├── vehicle_database.db     # SQLite database file
├── setup.sh               # Setup script
└── README.md              # Project documentation

Next Steps

  1. Explore the database using the query interface
  2. Add your own vehicle data
  3. Customize the schema if needed for your specific requirements
  4. Extend the Python scripts with additional functionality