consultoria-as
7b2a904498
- Migrate from SQLite to PostgreSQL with normalized schema - Add 11 lookup tables (fuel_type, body_type, drivetrain, transmission, materials, position_part, manufacture_type, quality_tier, countries, reference_type, shapes) - Rewrite dashboard/server.py (76 routes) using SQLAlchemy text() queries - Rewrite console/db.py (27 methods) using SQLAlchemy ORM - Add models.py with 27 SQLAlchemy model definitions - Add config.py for centralized DB_URL configuration - Add migrate_to_postgres.py migration script - Add docs/METABASE_GUIDE.md with complete data entry guide - Rebrand from "AUTOPARTS DB" to "NEXUS AUTOPARTS" - Fill vehicle data gaps via NHTSA API + heuristics: engines (cylinders, power, torque), brands (country, founded_year), models (body_type, production years), MYE (drivetrain, transmission, trim) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
426 lines
12 KiB
Markdown
426 lines
12 KiB
Markdown
# Documentación de Base de Datos - Nexus Autoparts
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## Resumen
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La base de datos utiliza SQLite 3 y está diseñada con un esquema normalizado para gestionar información de vehículos de manera eficiente.
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**Archivo:** `vehicle_database/vehicle_database.db`
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## Estadísticas Actuales
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| Tabla | Registros |
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|-------|-----------|
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| brands | 12 |
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| models | 10,923 |
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| engines | 10,919 |
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| years | ~35 |
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| model_year_engine | 12,075 |
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---
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## Diagrama Entidad-Relación
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```
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┌──────────────┐
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│ brands │
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├──────────────┤
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│ id (PK) │
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│ name │
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│ country │
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│ founded_year │
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│ created_at │
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└──────┬───────┘
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│
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│ 1:N
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│
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┌──────▼───────────────┐
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│ models │
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├──────────────────────┤
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│ id (PK) │
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│ brand_id (FK) │───────────────────────┐
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│ name │ │
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│ body_type │ │
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│ generation │ │
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│ production_start_year│ │
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│ production_end_year │ │
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│ created_at │ │
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└──────────────────────┘ │
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│
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┌──────────────────────┐ │
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│ years │ │
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├──────────────────────┤ │
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│ id (PK) │───────────────┐ │
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│ year │ │ │
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│ created_at │ │ │
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└──────────────────────┘ │ │
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│ │
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┌──────────────────────┐ │ │
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│ engines │ │ │
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├──────────────────────┤ │ │
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│ id (PK) │───────┐ │ │
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│ name │ │ │ │
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│ displacement_cc │ │ │ │
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│ cylinders │ │ │ │
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│ fuel_type │ │ │ │
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│ power_hp │ │ │ │
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│ torque_nm │ │ │ │
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│ engine_code │ │ │ │
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│ created_at │ │ │ │
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└──────────────────────┘ │ │ │
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│ │ │
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│ N:1 │ N:1 │ N:1
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│ │ │
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┌──────▼───────▼───────▼──────┐
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│ model_year_engine │
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├─────────────────────────────┤
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│ id (PK) │
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│ model_id (FK) │
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│ year_id (FK) │
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│ engine_id (FK) │
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│ trim_level │
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│ drivetrain │
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│ transmission │
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│ created_at │
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└─────────────────────────────┘
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```
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---
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## Definición de Tablas
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### Tabla: brands
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Almacena información de los fabricantes de vehículos.
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```sql
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CREATE TABLE brands (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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name TEXT NOT NULL UNIQUE,
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country TEXT,
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founded_year INTEGER,
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created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
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);
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```
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| Campo | Tipo | Restricciones | Descripción |
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|-------|------|---------------|-------------|
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| id | INTEGER | PK, AUTO | Identificador único |
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| name | TEXT | NOT NULL, UNIQUE | Nombre de la marca |
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| country | TEXT | - | País de origen |
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| founded_year | INTEGER | - | Año de fundación |
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| created_at | TIMESTAMP | DEFAULT NOW | Fecha de creación |
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**Índices:**
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- `idx_brands_name` en `name`
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---
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### Tabla: models
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Almacena información de los modelos de vehículos.
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```sql
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CREATE TABLE models (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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brand_id INTEGER NOT NULL,
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name TEXT NOT NULL,
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body_type TEXT,
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generation TEXT,
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production_start_year INTEGER,
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production_end_year INTEGER,
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created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
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FOREIGN KEY (brand_id) REFERENCES brands(id),
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UNIQUE(brand_id, name, generation)
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);
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```
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| Campo | Tipo | Restricciones | Descripción |
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|-------|------|---------------|-------------|
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| id | INTEGER | PK, AUTO | Identificador único |
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| brand_id | INTEGER | FK, NOT NULL | Referencia a brands |
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| name | TEXT | NOT NULL | Nombre del modelo |
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| body_type | TEXT | - | Tipo de carrocería |
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| generation | TEXT | - | Generación del modelo |
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| production_start_year | INTEGER | - | Año inicio producción |
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| production_end_year | INTEGER | - | Año fin producción |
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| created_at | TIMESTAMP | DEFAULT NOW | Fecha de creación |
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**Valores de body_type:**
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- Sedan, Coupe, Hatchback, SUV, Crossover, Truck, Van, Wagon, Convertible
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**Índices:**
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- `idx_models_brand_id` en `brand_id`
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- `idx_models_name` en `name`
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---
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### Tabla: engines
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Almacena especificaciones técnicas de los motores.
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```sql
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CREATE TABLE engines (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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name TEXT NOT NULL,
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displacement_cc INTEGER,
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cylinders INTEGER,
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fuel_type TEXT,
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power_hp INTEGER,
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torque_nm INTEGER,
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engine_code TEXT,
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created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
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UNIQUE(name, engine_code)
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);
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```
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| Campo | Tipo | Restricciones | Descripción |
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|-------|------|---------------|-------------|
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| id | INTEGER | PK, AUTO | Identificador único |
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| name | TEXT | NOT NULL | Nombre descriptivo |
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| displacement_cc | INTEGER | - | Cilindrada en cc |
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| cylinders | INTEGER | - | Número de cilindros |
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| fuel_type | TEXT | - | Tipo de combustible |
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| power_hp | INTEGER | - | Potencia en HP |
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| torque_nm | INTEGER | - | Torque en Nm |
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| engine_code | TEXT | - | Código del fabricante |
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| created_at | TIMESTAMP | DEFAULT NOW | Fecha de creación |
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**Valores de fuel_type:**
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- Gasoline, Diesel, Hybrid, Electric, Plug-in Hybrid, Flex Fuel
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**Índices:**
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- `idx_engines_name` en `name`
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- `idx_engines_code` en `engine_code`
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---
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### Tabla: years
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Tabla de referencia para años de producción.
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```sql
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CREATE TABLE years (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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year INTEGER NOT NULL UNIQUE,
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created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
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);
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```
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| Campo | Tipo | Restricciones | Descripción |
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|-------|------|---------------|-------------|
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| id | INTEGER | PK, AUTO | Identificador único |
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| year | INTEGER | NOT NULL, UNIQUE | Año |
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| created_at | TIMESTAMP | DEFAULT NOW | Fecha de creación |
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---
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### Tabla: model_year_engine
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Tabla de unión que relaciona modelos, años y motores.
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```sql
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CREATE TABLE model_year_engine (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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model_id INTEGER NOT NULL,
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year_id INTEGER NOT NULL,
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engine_id INTEGER NOT NULL,
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trim_level TEXT,
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drivetrain TEXT,
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transmission TEXT,
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created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
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FOREIGN KEY (model_id) REFERENCES models(id),
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FOREIGN KEY (year_id) REFERENCES years(id),
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FOREIGN KEY (engine_id) REFERENCES engines(id),
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UNIQUE(model_id, year_id, engine_id, trim_level)
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);
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```
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| Campo | Tipo | Restricciones | Descripción |
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|-------|------|---------------|-------------|
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| id | INTEGER | PK, AUTO | Identificador único |
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| model_id | INTEGER | FK, NOT NULL | Referencia a models |
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| year_id | INTEGER | FK, NOT NULL | Referencia a years |
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| engine_id | INTEGER | FK, NOT NULL | Referencia a engines |
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| trim_level | TEXT | - | Nivel de equipamiento |
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| drivetrain | TEXT | - | Tipo de tracción |
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| transmission | TEXT | - | Tipo de transmisión |
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| created_at | TIMESTAMP | DEFAULT NOW | Fecha de creación |
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**Valores de drivetrain:**
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- FWD (Front-Wheel Drive), RWD (Rear-Wheel Drive), AWD (All-Wheel Drive), 4WD (Four-Wheel Drive)
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**Valores de transmission:**
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- Manual, Automatic, CVT, DCT, AMT
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**Índices:**
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- `idx_mye_model_id` en `model_id`
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- `idx_mye_year_id` en `year_id`
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- `idx_mye_engine_id` en `engine_id`
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---
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## Consultas Comunes
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### Obtener todos los vehículos de una marca
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```sql
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SELECT
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b.name AS brand,
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m.name AS model,
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y.year,
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e.name AS engine,
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mye.trim_level,
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mye.drivetrain,
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mye.transmission
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FROM model_year_engine mye
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JOIN models m ON mye.model_id = m.id
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JOIN brands b ON m.brand_id = b.id
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JOIN years y ON mye.year_id = y.id
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JOIN engines e ON mye.engine_id = e.id
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WHERE b.name = 'Toyota'
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ORDER BY m.name, y.year;
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```
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### Buscar vehículos por año
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```sql
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SELECT
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b.name AS brand,
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m.name AS model,
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e.name AS engine,
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e.power_hp,
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mye.trim_level
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FROM model_year_engine mye
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JOIN models m ON mye.model_id = m.id
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JOIN brands b ON m.brand_id = b.id
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JOIN years y ON mye.year_id = y.id
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JOIN engines e ON mye.engine_id = e.id
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WHERE y.year = 2020;
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```
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### Obtener especificaciones de motor
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```sql
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SELECT
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name,
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displacement_cc,
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cylinders,
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fuel_type,
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power_hp,
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torque_nm,
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engine_code
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FROM engines
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WHERE cylinders = 6
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ORDER BY power_hp DESC;
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```
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### Contar modelos por marca
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```sql
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SELECT
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b.name AS brand,
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COUNT(DISTINCT m.id) AS model_count
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FROM brands b
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LEFT JOIN models m ON b.id = m.brand_id
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GROUP BY b.id
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ORDER BY model_count DESC;
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```
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### Buscar motores por potencia
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```sql
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SELECT *
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FROM engines
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WHERE power_hp >= 300
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ORDER BY power_hp DESC;
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```
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---
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## Mantenimiento
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### Backup de la Base de Datos
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```bash
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# Crear backup
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sqlite3 vehicle_database.db ".backup 'backup.db'"
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# O usando cp
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cp vehicle_database.db vehicle_database_backup_$(date +%Y%m%d).db
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```
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### Optimización
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```sql
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-- Analizar tablas para optimizar consultas
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ANALYZE;
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-- Reconstruir índices
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REINDEX;
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-- Compactar base de datos
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VACUUM;
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```
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### Verificar Integridad
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```sql
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PRAGMA integrity_check;
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PRAGMA foreign_key_check;
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```
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---
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## Conexión desde Python
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```python
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import sqlite3
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# Conectar a la base de datos
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conn = sqlite3.connect('vehicle_database/vehicle_database.db')
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conn.row_factory = sqlite3.Row # Permite acceso por nombre de columna
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# Crear cursor
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cursor = conn.cursor()
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# Ejecutar consulta
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cursor.execute("""
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SELECT b.name, m.name, y.year
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FROM model_year_engine mye
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JOIN models m ON mye.model_id = m.id
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JOIN brands b ON m.brand_id = b.id
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JOIN years y ON mye.year_id = y.id
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WHERE b.name = ?
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""", ('Toyota',))
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# Obtener resultados
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for row in cursor.fetchall():
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print(f"{row['name']} - {row['name']} ({row['year']})")
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# Cerrar conexión
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conn.close()
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```
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---
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## Migración de Datos
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### Exportar a CSV
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```bash
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sqlite3 -header -csv vehicle_database.db "SELECT * FROM brands;" > brands_export.csv
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sqlite3 -header -csv vehicle_database.db "SELECT * FROM models;" > models_export.csv
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sqlite3 -header -csv vehicle_database.db "SELECT * FROM engines;" > engines_export.csv
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```
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### Importar desde CSV
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```bash
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sqlite3 vehicle_database.db <<EOF
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.mode csv
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.import brands.csv brands
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.import models.csv models
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.import engines.csv engines
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EOF
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```
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