Static Data Modeling

Relevant source files

The following files were used as context for generating this wiki page:

• data/fleet.ts
• components/CarCard.tsx
• components/FleetFilters.tsx
• app/fleet/page.tsx
• app/fleet/[slug]/page.tsx
• components/RequestForm.tsx

Static Data Modeling in the AVP Supercars project refers to the structural definition and centralized storage of vehicle information, used throughout the application to drive the fleet display, filtering systems, and booking requests. Instead of a dynamic database, the project utilizes a strongly-typed TypeScript registry to maintain "Monaco-level" consistency across its luxury vehicle offerings.

This modeling approach ensures that every vehicle in the fleet adheres to a specific schema, encompassing technical specifications, categorization, and visual assets. This data serves as the single source of truth for the Fleet Page and individual Car Detail Pages.

Sources: data/fleet.ts:1-20, app/fleet/page.tsx:14

Core Data Structures

The system architecture relies on three primary TypeScript types that define the shape of the vehicle data. These types ensure type safety when passing car information between components like CarCard and FleetFilters.

The Car Schema

The Car type is the central entity, aggregating technical highlights and visual media.

Field	Type	Description
slug	string	Unique identifier used for URL routing and lookup.
brand	string	The manufacturer of the vehicle (e.g., Ferrari, Audi).
model	string	Specific model name.
category	string	Classification for filtering (e.g., GT, Supercar, SUV).
tagline	string	A short, marketing-focused description.
images	CarImage[]	Array of source paths and alt text for gallery display.
bullets	string[]	Key service features or rental terms.
highlights	CarHighlight[]	Key-value pairs for technical specs (HP, 0-100, etc.).

Sources: data/fleet.ts:1-20

Visual and Technical Sub-types

To maintain granularity, images and specifications are modeled as distinct objects:

• CarImage: Stores src (URL/path) and alt (accessibility text).
• CarHighlight: Stores a label (e.g., "Engine") and a value (e.g., "5.2L V10").

Sources: data/fleet.ts:1-10

Data Relationships and Hierarchy

The data is organized as a flat array of objects exported as fleet. This structure allows for efficient filtering and direct access via unique slugs.

The following class diagram illustrates the relationships between the data types:

The diagram shows that a Car entity acts as a container for multiple image assets and technical highlights.
Sources: data/fleet.ts:1-25

Data Flow and Consumption

The static data modeled in data/fleet.ts flows through the application in two primary patterns: list filtering and detail retrieval.

List and Filter Flow

On the main fleet page, the entire fleet array is loaded and passed to the FleetFilters component. This component computes unique categories dynamically from the static data and provides a filtered subset back to the UI.

The flow shows how static data is transformed into a dynamic user interface through state management and filtering logic.
Sources: app/fleet/page.tsx:14-20, components/FleetFilters.tsx:13-33

Detail Retrieval Logic

Individual vehicle pages use the slug parameter from the URL to perform a lookup in the static fleet array. If no match is found, the system triggers a notFound() response.

// Example of static data retrieval via slug
const car = fleet.find((c) => c.slug === slug);
if (!car) return notFound();

Sources: app/fleet/[slug]/page.tsx:13-16

Integration with Booking Systems

The static modeling extends into the user interaction layer. When a user views a specific vehicle and initiates a request, the brand and model fields from the static data are used to pre-populate the RequestForm.

• Pre-population: The slug page passes the car's name as a defaultCar prop to the RequestForm.
• Message Generation: The form uses the static model fields to construct a formatted WhatsApp or Email string.

Sources: components/RequestForm.tsx:37-60, app/fleet/[slug]/page.tsx:28-30

Summary of Fleet Categories

The static model currently supports several high-level categories used for organization and filtering.

Category	Typical Highlights	Featured Models
GT	Engine, Power, Seats	Ferrari Portofino, GTC4Lusso T
Supercar	0-100 km/h, Drive	Audi R8 Spyder
Luxury SUV	Seats, Comfort	Aston Martin DBX
Performance	Engine, Turbo	Audi RS3, RSQ8

Sources: data/fleet.ts:28-154

The static data modeling in this project provides a robust, type-safe foundation for presenting luxury inventory. By centralizing vehicle attributes in a structured TypeScript module, the application achieves high performance and consistency without the overhead of a database for its relatively stable fleet information.