consultoria-as
f395d67136
- 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
82 lines
2.6 KiB
Markdown
82 lines
2.6 KiB
Markdown
# Vehicle Database - Getting Started Guide
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## Overview
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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.
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## Database Structure
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The database consists of five main tables:
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- **brands**: Vehicle manufacturers (Toyota, Ford, etc.)
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- **models**: Vehicle models (Camry, F-150, etc.)
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- **engines**: Engine specifications (2JZ-GTE, EcoBoost, etc.)
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- **years**: Calendar years for vehicle production
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- **model_year_engine**: Junction table linking all entities with trim levels and specifications
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## Setup and Usage
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### 1. Initial Setup
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Run the setup script to initialize the database:
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```bash
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cd vehicle_database
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./setup.sh
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```
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### 2. Querying the Database
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Use the interactive query interface:
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```bash
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python3 scripts/query_interface.py
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```
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The query interface allows you to:
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- Search for vehicles by brand, model, year, or engine
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- Browse all available brands
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- View models for specific brands
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- See production years for specific models
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### 3. Managing the Database
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Use the database manager for programmatic access:
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```bash
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python3 scripts/database_manager.py
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```
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### 4. Importing Data
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To import data from CSV files:
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1. Prepare your data in the required CSV format
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2. Use the CSV importer functionality in your own scripts
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Sample CSV files are provided in the `data/` directory.
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## Example Queries
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The system supports various search options:
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- Find all vehicles by a specific brand
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- Search for a specific model across all years
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- Filter by engine type or specifications
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- Look up trim levels and drivetrain configurations
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## Extending the Database
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To add more data:
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1. Use the Python API in `scripts/database_manager.py`
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2. Directly execute SQL commands on the SQLite database
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3. Import data from CSV files using the structure provided
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## File Structure
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```
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vehicle_database/
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├── sql/
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│ └── schema.sql # Database schema
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├── scripts/
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│ ├── database_manager.py # Main database manager
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│ ├── query_interface.py # Interactive query interface
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│ └── csv_importer.py # CSV import functionality
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├── data/ # Sample CSV data files
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├── vehicle_database.db # SQLite database file
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├── setup.sh # Setup script
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└── README.md # Project documentation
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```
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## Next Steps
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1. Explore the database using the query interface
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2. Add your own vehicle data
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3. Customize the schema if needed for your specific requirements
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4. Extend the Python scripts with additional functionality |