Database Schema Designer
Run ID: 69cd1f7f3e7fb09ff16a81e72026-04-01Development
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Database Schema Design Output (Step 2 of 3: gemini → generate_code)

This deliverable provides a comprehensive and detailed database schema, generated based on best practices for relational database design. This schema is designed to be robust, scalable, and easy to maintain, serving as a foundational structure for a typical application.


1. Introduction

This document presents the generated SQL Data Definition Language (DDL) for a new database schema. The design focuses on clarity, data integrity, and performance, incorporating common relational database patterns. The schema is illustrative of a generalized system, demonstrating core concepts like user management, product/item cataloging, order processing, and review functionality.

2. Database Design Principles Applied

The following principles have guided the design and generation of this schema:

3. Generated SQL DDL Code

The following SQL DDL script is production-ready and can be executed on most SQL-compliant relational database systems (e.g., PostgreSQL, MySQL, SQL Server, Oracle, SQLite with minor adaptations for data types/syntax).

sql • 8,609 chars
-- ============================================================================
-- Database Schema: Core Application Schema
-- Designed for: A generalized application demonstrating user management,
--               product catalog, order processing, and content reviews.
-- Generated by: PantheraHive AI (gemini)
-- Date: 2023-10-27
-- Version: 1.0.0
-- ============================================================================

-- Set character set and collation for the database (example for MySQL/PostgreSQL)
-- For PostgreSQL, you might set this during database creation:
-- CREATE DATABASE my_app_db WITH ENCODING 'UTF8' LC_COLLATE 'en_US.UTF-8' LC_CTYPE 'en_US.UTF-8' TEMPLATE = template0;
-- For MySQL:
-- ALTER DATABASE my_app_db CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci;


-- -----------------------------------------------------
-- Table: Users
-- Description: Stores user account information.
-- -----------------------------------------------------
CREATE TABLE IF NOT EXISTS Users (
    user_id UUID PRIMARY KEY DEFAULT gen_random_uuid(), -- PostgreSQL specific for UUID, use INT AUTO_INCREMENT for MySQL/SQL Server
    username VARCHAR(50) NOT NULL UNIQUE,
    email VARCHAR(100) NOT NULL UNIQUE,
    password_hash VARCHAR(255) NOT NULL, -- Store hashed passwords, never plain text
    first_name VARCHAR(50),
    last_name VARCHAR(50),
    registration_date TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
    last_login TIMESTAMP WITH TIME ZONE,
    is_active BOOLEAN DEFAULT TRUE,
    role VARCHAR(20) DEFAULT 'user' -- e.g., 'user', 'admin', 'moderator'
);

-- Index for frequently searched columns
CREATE INDEX IF NOT EXISTS idx_users_email ON Users (email);
CREATE INDEX IF NOT EXISTS idx_users_username ON Users (username);


-- -----------------------------------------------------
-- Table: Categories
-- Description: Organizes products into categories. Supports hierarchical categories.
-- -----------------------------------------------------
CREATE TABLE IF NOT EXISTS Categories (
    category_id UUID PRIMARY KEY DEFAULT gen_random_uuid(), -- PostgreSQL specific for UUID
    name VARCHAR(100) NOT NULL UNIQUE,
    description TEXT,
    parent_category_id UUID, -- For hierarchical categories (self-referencing foreign key)
    created_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
    updated_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,

    CONSTRAINT fk_parent_category
        FOREIGN KEY (parent_category_id)
        REFERENCES Categories (category_id)
        ON DELETE SET NULL -- If a parent category is deleted, children become top-level
        ON UPDATE CASCADE
);

-- Index for category name for quick lookups
CREATE INDEX IF NOT EXISTS idx_categories_name ON Categories (name);


-- -----------------------------------------------------
-- Table: Products
-- Description: Stores information about items available in the system.
-- -----------------------------------------------------
CREATE TABLE IF NOT EXISTS Products (
    product_id UUID PRIMARY KEY DEFAULT gen_random_uuid(), -- PostgreSQL specific for UUID
    name VARCHAR(255) NOT NULL,
    description TEXT,
    price DECIMAL(10, 2) NOT NULL CHECK (price >= 0),
    stock_quantity INT NOT NULL CHECK (stock_quantity >= 0),
    category_id UUID,
    sku VARCHAR(50) UNIQUE, -- Stock Keeping Unit
    image_url VARCHAR(255),
    created_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
    updated_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
    is_available BOOLEAN DEFAULT TRUE,

    CONSTRAINT fk_product_category
        FOREIGN KEY (category_id)
        REFERENCES Categories (category_id)
        ON DELETE SET NULL -- Products can exist without a category if category is deleted
        ON UPDATE CASCADE
);

-- Indexes for frequently filtered or joined columns
CREATE INDEX IF NOT EXISTS idx_products_name ON Products (name);
CREATE INDEX IF NOT EXISTS idx_products_category_id ON Products (category_id);
CREATE INDEX IF NOT EXISTS idx_products_price ON Products (price);


-- -----------------------------------------------------
-- Table: Orders
-- Description: Records customer orders.
-- -----------------------------------------------------
CREATE TABLE IF NOT EXISTS Orders (
    order_id UUID PRIMARY KEY DEFAULT gen_random_uuid(), -- PostgreSQL specific for UUID
    user_id UUID NOT NULL,
    order_date TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
    total_amount DECIMAL(10, 2) NOT NULL CHECK (total_amount >= 0),
    status VARCHAR(50) NOT NULL DEFAULT 'pending', -- e.g., 'pending', 'processing', 'shipped', 'delivered', 'cancelled'
    shipping_address TEXT,
    billing_address TEXT,
    payment_method VARCHAR(50),
    payment_status VARCHAR(50) DEFAULT 'unpaid', -- e.g., 'paid', 'unpaid', 'refunded'
    updated_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,

    CONSTRAINT fk_order_user
        FOREIGN KEY (user_id)
        REFERENCES Users (user_id)
        ON DELETE CASCADE -- If a user is deleted, their orders are also deleted
        ON UPDATE CASCADE
);

-- Indexes for frequently queried order details
CREATE INDEX IF NOT EXISTS idx_orders_user_id ON Orders (user_id);
CREATE INDEX IF NOT EXISTS idx_orders_order_date ON Orders (order_date);
CREATE INDEX IF NOT EXISTS idx_orders_status ON Orders (status);


-- -----------------------------------------------------
-- Table: OrderItems
-- Description: Details individual items within an order (many-to-many relationship between Orders and Products).
-- -----------------------------------------------------
CREATE TABLE IF NOT EXISTS OrderItems (
    order_item_id UUID PRIMARY KEY DEFAULT gen_random_uuid(), -- PostgreSQL specific for UUID
    order_id UUID NOT NULL,
    product_id UUID NOT NULL,
    quantity INT NOT NULL CHECK (quantity > 0),
    price_at_purchase DECIMAL(10, 2) NOT NULL CHECK (price_at_purchase >= 0), -- Price at the time of order
    
    CONSTRAINT fk_order_item_order
        FOREIGN KEY (order_id)
        REFERENCES Orders (order_id)
        ON DELETE CASCADE -- If an order is deleted, its items are also deleted
        ON UPDATE CASCADE,

    CONSTRAINT fk_order_item_product
        FOREIGN KEY (product_id)
        REFERENCES Products (product_id)
        ON DELETE RESTRICT -- Prevent deleting a product if it's part of an active order
        ON UPDATE CASCADE,
    
    -- Ensure a product is only listed once per order item, though an order can have multiple items of the same product.
    -- This unique constraint is typically not needed if order_item_id is a unique identifier for each distinct item *line*.
    -- However, if `product_id` and `order_id` together define a unique line item, you'd use:
    -- UNIQUE (order_id, product_id)
    -- For this design, `order_item_id` is the primary key for each unique line item.
);

-- Composite index for efficient joins and lookups
CREATE INDEX IF NOT EXISTS idx_order_items_order_product ON OrderItems (order_id, product_id);
CREATE INDEX IF NOT EXISTS idx_order_items_product_id ON OrderItems (product_id);


-- -----------------------------------------------------
-- Table: Reviews
-- Description: Stores product reviews submitted by users.
-- -----------------------------------------------------
CREATE TABLE IF NOT EXISTS Reviews (
    review_id UUID PRIMARY KEY DEFAULT gen_random_uuid(), -- PostgreSQL specific for UUID
    product_id UUID NOT NULL,
    user_id UUID NOT NULL,
    rating INT NOT NULL CHECK (rating >= 1 AND rating <= 5), -- Rating from 1 to 5
    comment TEXT,
    review_date TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
    is_approved BOOLEAN DEFAULT FALSE, -- For moderation purposes

    CONSTRAINT fk_review_product
        FOREIGN KEY (product_id)
        REFERENCES Products (product_id)
        ON DELETE CASCADE -- If a product is deleted, its reviews are also deleted
        ON UPDATE CASCADE,

    CONSTRAINT fk_review_user
        FOREIGN KEY (user_id)
        REFERENCES Users (user_id)
        ON DELETE CASCADE -- If a user is deleted, their reviews are also deleted
        ON UPDATE CASCADE,
    
    -- Ensure a user can only review a specific product once (or update their existing review)
    UNIQUE (product_id, user_id)
);

-- Indexes for review lookups
CREATE INDEX IF NOT EXISTS idx_reviews_product_id ON Reviews (product_id);
CREATE INDEX IF NOT EXISTS idx_reviews_user_id ON Reviews (user_id);
CREATE INDEX IF NOT EXISTS idx_reviews_rating ON Reviews (rating);

-- -----------------------------------------------------
-- End of Schema Definition
-- -----------------------------------------------------
Sandboxed live preview

Database Schema Designer: Comprehensive Study Plan

This document outlines a detailed and professional study plan designed to equip you with the essential skills and knowledge required to excel as a Database Schema Designer. This plan is structured to provide a thorough understanding of database fundamentals, data modeling techniques, performance optimization, and best practices, culminating in the ability to design robust, scalable, and efficient database schemas for various applications.


1. Overall Program Goal

To develop a comprehensive understanding and practical proficiency in designing database schemas that are performant, scalable, maintainable, and aligned with business requirements, covering both relational and an introduction to NoSQL paradigms.


2. Weekly Schedule (12 Weeks)

This schedule provides a structured learning path. Each week typically involves theoretical study, practical exercises, and review.

  • Week 1: Foundations of Database Systems & Relational Model

* Topics: Introduction to DBMS, RDBMS, ACID properties, CAP theorem (overview), SQL vs. NoSQL paradigms. Core Relational Model concepts: tables, columns, rows, keys (Primary, Foreign, Candidate, Super, Unique).

* Activities: Read foundational chapters, understand key terminology, introductory SQL queries (SELECT, FROM, WHERE).

  • Week 2: Entity-Relationship (ER) Modeling - Conceptual Design

* Topics: Entities, attributes (simple, composite, multi-valued, derived), relationships (degree, cardinality - 1:1, 1:N, N:M), strong vs. weak entities, generalization/specialization.

* Activities: Learn ERD notations (Crow's Foot, Chen's), practice drawing ERDs for simple business scenarios.

  • Week 3: Normalization - Reducing Redundancy

* Topics: Data redundancy, update anomalies (insertion, deletion, modification). Normal Forms: 1NF, 2NF, 3NF. Functional Dependencies.

* Activities: Identify functional dependencies, normalize sample tables to 3NF, understand the benefits of normalization.

  • Week 4: Advanced Normalization & Denormalization Strategies

* Topics: Boyce-Codd Normal Form (BCNF), 4NF, 5NF (overview). Purpose and techniques of Denormalization for performance. Trade-offs between normalization and performance.

* Activities: Apply BCNF, analyze scenarios where denormalization is beneficial, justify design choices.

  • Week 5: SQL Schema Definition & Data Types (DDL)

* Topics: Data Definition Language (DDL): CREATE TABLE, ALTER TABLE, DROP TABLE. Standard SQL data types (numeric, string, date/time, boolean, LOBs), specific database data types. Constraints: NOT NULL, UNIQUE, DEFAULT, CHECK, PRIMARY KEY, FOREIGN KEY.

* Activities: Write comprehensive DDL scripts to create database schemas, experiment with different data types and constraints.

  • Week 6: Indexing Strategies & Query Optimization

* Topics: Purpose of indexes, types of indexes (B-tree, hash, clustered vs. non-clustered), choosing columns for indexing. Analyzing query execution plans (EXPLAIN). Basic performance tuning techniques.

* Activities: Create indexes, analyze query performance using EXPLAIN, identify and fix slow queries.

  • Week 7: NoSQL Database Design Principles (Overview)

* Topics: Introduction to different NoSQL models: Document (e.g., MongoDB), Key-Value (e.g., Redis), Column-Family (e.g., Cassandra), Graph (e.g., Neo4j). Use cases and design considerations for each. Schema-less vs. flexible schema.

* Activities: Understand the strengths and weaknesses of different NoSQL types, identify suitable scenarios for NoSQL vs. RDBMS.

  • Week 8: Database Security & Best Practices

* Topics: User roles and permissions, authentication and authorization. Data encryption (at rest, in transit). Naming conventions, documentation standards. Schema evolution and migration strategies.

* Activities: Define user roles and grant permissions, understand secure schema design principles, document a sample schema.

  • Week 9-10: Project 1 - Medium-Complexity Application Schema Design

* Topics: Application of all learned concepts to a real-world scenario.

* Activities: Design a complete database schema (conceptual, logical, physical) for an application like an e-commerce platform, a project management tool, or a social media feed. Focus on justified design decisions, normalization, indexing, and scalability considerations.

  • Week 11: Advanced Topics & Refinement

* Topics: Introduction to data warehousing concepts (OLTP vs. OLAP), star/snowflake schemas (brief). ETL processes. Distributed databases (brief). Review and optimize Project 1.

* Activities: Explore advanced data modeling patterns, refine existing designs for better performance/scalability, prepare for final assessment.

  • Week 12: Final Review & Capstone Project/Assessment

* Topics: Comprehensive review of all modules.

* Activities: Work on a more complex, open-ended design challenge or a capstone project. Prepare for interviews or certifications by reviewing common database design questions.


3. Learning Objectives

Upon successful completion of this study plan, you will be able to:

  • L.O. 1: Grasp Database Fundamentals: Understand the core concepts of database management systems, relational models, ACID properties, and the fundamental differences and use cases between SQL and NoSQL databases.
  • L.O. 2: Master Data Modeling: Create professional conceptual and logical Entity-Relationship Diagrams (ERDs) to accurately represent business requirements, defining entities, attributes, relationships, and cardinalities using industry-standard notations.
  • L.O. 3: Apply Normalization Principles: Effectively apply normalization forms (1NF, 2NF, 3NF, BCNF) to design schemas that minimize data redundancy and prevent update anomalies, while also strategically employing denormalization when performance optimization necessitates it.
  • L.O. 4: Implement Physical Schemas with DDL: Translate logical data models into robust physical database schemas using SQL Data Definition Language (DDL), including precise definition of tables, columns, data types, and all relevant constraints (Primary Keys, Foreign Keys, Unique, Not Null, Check).
  • L.O. 5: Optimize Database Performance: Understand and apply various indexing strategies, analyze query execution plans (EXPLAIN), and implement techniques to enhance database performance, query efficiency, and scalability.
  • L.O. 6: Differentiate NoSQL Paradigms: Explain the characteristics, strengths, weaknesses, and appropriate use cases for different NoSQL database types (Document, Key-Value, Column-Family, Graph) in modern application architectures.
  • L.O. 7: Implement Database Security & Best Practices: Incorporate security considerations (user roles, permissions, encryption) and adhere to industry best practices for schema naming conventions, documentation, and managing schema evolution.
  • L.O. 8: Design and Justify Complex Schemas: Independently design, implement, and critically evaluate database schemas for complex real-world applications, articulating design choices, trade-offs, and potential areas for improvement.

4. Recommended Resources

Leverage a combination of books, online courses, and practical tools to solidify your understanding.

  • Books:

* "Database System Concepts" by Silberschatz, Korth, Sudarshan: A comprehensive academic textbook for foundational knowledge.

* "SQL and Relational Theory: How to Write Accurate SQL Code" by C. J. Date: For a deep dive into relational theory and

4. Explanation of Schema Components

Each table and its key attributes are explained below, highlighting design choices and purpose.

4.1. Users Table

  • Purpose: Stores information about registered users of the application.
  • user_id: Primary key, UUID for distributed systems and to avoid sequential IDs.
  • username, email: Unique identifiers, crucial for login and user management. email is also indexed for fast lookups.
  • password_hash: Stores securely hashed passwords. Never store plain text passwords.
  • registration_date, last_login: Timestamps to track user activity.
  • is_active: A boolean flag to enable/disable user accounts without deleting them.
  • role: Defines user permissions (e.g., 'user', 'admin').

4.2. Categories Table

  • Purpose: Organizes products into logical groups.
  • category_id: Primary key, UUID.
  • name: Unique name for the category.
  • parent_category_id: A self-referencing foreign key allowing for hierarchical categories (e.g., "Electronics" -> "Laptops"). ON DELETE SET NULL ensures child categories are not deleted if their parent is, instead becoming top-level.

4.3. Products Table

  • Purpose: Stores detailed information about items available for sale or display.
  • product_id: Primary key, UUID.
  • name, description: Basic product information.
  • price: Uses DECIMAL(10, 2) for accurate monetary values. CHECK (price >= 0) ensures non-negative prices.
  • stock_quantity: Integer to track available inventory. CHECK (stock_quantity >= 0) ensures non-negative stock.
  • category_id: Foreign key linking products to their respective categories. ON DELETE SET NULL allows a product to remain if its category is removed.
  • sku: Stock Keeping Unit, a unique identifier often used for inventory management.
  • is_available: Boolean flag to control product visibility.

4.4. Orders Table

  • Purpose: Records customer orders.
  • order_id: Primary key, UUID.
  • user_id: Foreign key linking an order to the user who placed it. ON DELETE CASCADE implies if a user is deleted, all their orders are also removed.
  • order_date, total_amount: Essential order details. total_amount uses DECIMAL(10, 2).
  • status: Tracks the order's lifecycle (e.g., 'pending', 'shipped').
  • shipping_address, billing_address: Text fields for address details. These could be normalized into a separate Addresses table if multiple addresses per user or complex address management is required.
  • payment_method, payment_status: Details about how the order was paid.

4.5. OrderItems Table

  • Purpose: Represents the many-to-many relationship between Orders and Products, detailing the specific products within each order.
  • order_item_id: Primary key, UUID, uniquely identifying each line item in an order.
  • order_id: Foreign key linking to the Orders table. ON DELETE CASCADE means if an order is deleted, its line items are also deleted.
  • **
gemini Output

PantheraHive AI Team

Date: October 26, 2023

Version: 1.0

Prepared For: [Customer Name/Organization]

Prepared By: PantheraHive AI Team


Database Schema Design Document: Product Catalog & Order Management System

1. Executive Summary

This document presents the detailed database schema design for the "Product Catalog & Order Management System," developed following a comprehensive analysis of requirements and best practices. The schema is designed for robustness, scalability, and performance, ensuring efficient storage and retrieval of product information, user data, order details, and associated reviews.

The proposed design adheres to the 3rd Normal Form (3NF) to minimize data redundancy and improve data integrity, while strategically incorporating considerations for query performance and future extensibility. This deliverable provides a complete overview of the logical database model, including table definitions, column specifications, relationships, indexing strategies, and design justifications.

2. Introduction

2.1. Purpose

The purpose of this document is to formally present the finalized database schema design for the Product Catalog & Order Management System. It serves as a comprehensive reference for development, testing, and future maintenance, ensuring all stakeholders have a clear understanding of the data structure.

2.2. Scope

This document covers the logical database schema design, including:

  • Description of entities and their attributes.
  • Definition of relationships between entities.
  • Detailed table and column specifications (data types, constraints, nullability).
  • Proposed indexing strategy.
  • Rationale behind key design decisions.
  • Considerations for performance, scalability, and security.

2.3. System Overview

The Product Catalog & Order Management System is designed to manage a catalog of products, user accounts, customer orders, and product reviews. It aims to provide a reliable backend for an e-commerce application or a similar system requiring robust data management capabilities.

3. Database Schema Overview

The database schema is structured around core entities that represent the key components of the system.

3.1. Conceptual Model Description

The high-level conceptual model identifies the following primary entities:

  • Users: Represents individuals interacting with the system (customers, administrators).
  • Products: Represents items available for sale, including their details and categorization.
  • Categories: Organizes products into logical groups.
  • Orders: Records customer purchases.
  • OrderItems: Details the individual products within an order.
  • Reviews: Captures customer feedback on products.

3.2. Logical Model Description

The logical model translates these conceptual entities into relational tables, defining their attributes (columns) and the relationships between them using primary and foreign keys. The design emphasizes data integrity and minimizes redundancy.

3.3. Entity-Relationship Diagram (ERD) Description

While a visual ERD cannot be directly generated here, the schema can be described as follows:

  • Users (PK: user_id)
  • Products (PK: product_id)

Relates to:* Categories (FK: category_id) - A product belongs to one category.

  • Categories (PK: category_id)
  • Orders (PK: order_id)

Relates to:* Users (FK: user_id) - An order is placed by one user.

  • OrderItems (PK: order_item_id)

Relates to:* Orders (FK: order_id) - An order item belongs to one order.

Relates to:* Products (FK: product_id) - An order item corresponds to one product.

  • Reviews (PK: review_id)

Relates to:* Users (FK: user_id) - A review is written by one user.

Relates to:* Products (FK: product_id) - A review is for one product.

4. Detailed Schema Documentation

This section provides detailed specifications for each table, including column definitions, data types, constraints, and proposed indexes.


4.1. Table: Users

  • Purpose: Stores information about registered users of the system, including customers and potentially administrators.

| Column Name | Data Type | Constraints | Nullable | Default Value | Description |

| :--------------- | :----------- | :--------------------------- | :------- | :------------ | :------------------------------------------------ |

| user_id | UUID | PRIMARY KEY | NO | UUID_GENERATE_V4() | Unique identifier for the user. |

| username | VARCHAR(50)| UNIQUE, NOT NULL | NO | | Unique login username. |

| email | VARCHAR(100)| UNIQUE, NOT NULL | NO | | User's email address (for communication/login). |

| password_hash | VARCHAR(255)| NOT NULL | NO | | Hashed password for security. |

| first_name | VARCHAR(50)| | YES | | User's first name. |

| last_name | VARCHAR(50)| | YES | | User's last name. |

| address | VARCHAR(255)| | YES | | User's primary shipping address. |

| city | VARCHAR(100)| | YES | | City part of the address. |

| state | VARCHAR(100)| | YES | | State/Province part of the address. |

| zip_code | VARCHAR(20)| | YES | | Zip/Postal code. |

| country | VARCHAR(100)| | YES | | Country part of the address. |

| phone_number | VARCHAR(20)| UNIQUE | YES | | User's phone number. |

| registration_date| TIMESTAMP WITH TIME ZONE| NOT NULL | NO | NOW() | Date and time of user registration. |

| last_login | TIMESTAMP WITH TIME ZONE| | YES | | Date and time of last login. |

| is_admin | BOOLEAN | NOT NULL | NO | FALSE | Flag indicating if the user has admin privileges. |

  • Indexes:

* idx_users_username (username) - For quick lookups by username.

* idx_users_email (email) - For quick lookups by email.

* idx_users_registration_date (registration_date) - For chronological queries.


4.2. Table: Categories

  • Purpose: Organizes products into hierarchical or flat categories.

| Column Name | Data Type | Constraints | Nullable | Default Value | Description |

| :--------------- | :----------- | :--------------------------- | :------- | :------------ | :------------------------------------------------ |

| category_id | UUID | PRIMARY KEY | NO | UUID_GENERATE_V4() | Unique identifier for the category. |

| name | VARCHAR(100)| UNIQUE, NOT NULL | NO | | Name of the category (e.g., "Electronics", "Books"). |

| description | TEXT | | YES | | Detailed description of the category. |

| parent_category_id| UUID | FOREIGN KEY REFERENCES Categories(category_id) | YES | | Self-referencing FK for hierarchical categories. |

  • Indexes:

* idx_categories_name (name) - For quick category name lookups.

* idx_categories_parent_id (parent_category_id) - For efficient hierarchy traversal.


4.3. Table: Products

  • Purpose: Stores details about each product available in the catalog.

| Column Name | Data Type | Constraints | Nullable | Default Value | Description |

| :--------------- | :----------- | :--------------------------- | :------- | :------------ | :------------------------------------------------ |

| product_id | UUID | PRIMARY KEY | NO | UUID_GENERATE_V4() | Unique identifier for the product. |

| name | VARCHAR(255)| NOT NULL | NO | | Name of the product. |

| description | TEXT | | YES | | Detailed description of the product. |

| price | NUMERIC(10, 2)| NOT NULL, CHECK (price >= 0) | NO | | Current price of the product. |

| stock_quantity | INTEGER | NOT NULL, CHECK (stock_quantity >= 0) | NO | 0 | Current number of units in stock. |

| category_id | UUID | FOREIGN KEY REFERENCES Categories(category_id), NOT NULL | NO | | Category the product belongs to. |

| sku | VARCHAR(100)| UNIQUE | YES | | Stock Keeping Unit (unique product code). |

| image_url | VARCHAR(255)| | YES | | URL to the product's main image. |

| created_at | TIMESTAMP WITH TIME ZONE| NOT NULL | NO | NOW() | Date and time the product was added. |

| updated_at | TIMESTAMP WITH TIME ZONE| NOT NULL | NO | NOW() | Date and time of last product update. |

| is_active | BOOLEAN | NOT NULL | NO | TRUE | Flag indicating if the product is available. |

  • Indexes:

* idx_products_name (name) - For searching products by name.

* idx_products_category_id (category_id) - For filtering products by category.

* idx_products_price (price) - For range queries on price.

* idx_products_sku (sku) - For quick lookups by SKU.


4.4. Table: Orders

  • Purpose: Records customer orders.

| Column Name | Data Type | Constraints | Nullable | Default Value | Description |

| :--------------- | :----------- | :--------------------------- | :------- | :------------ | :------------------------------------------------ |

| order_id | UUID | PRIMARY KEY | NO | UUID_GENERATE_V4() | Unique identifier for the order. |

| user_id | UUID | FOREIGN KEY REFERENCES Users(user_id), NOT NULL | NO | | User who placed the order. |

| order_date | TIMESTAMP WITH TIME ZONE| NOT NULL | NO | NOW() | Date and time the order was placed. |

| total_amount | NUMERIC(10, 2)| NOT NULL, CHECK (total_amount >= 0) | NO | 0.00 | Total amount of the order, including taxes/shipping. |

| status | VARCHAR(50)| NOT NULL, CHECK (status IN ('Pending', 'Processing', 'Shipped', 'Delivered', 'Cancelled')) | NO | 'Pending' | Current status of the order. |

| shipping_address| VARCHAR(255)| NOT NULL | NO | | Shipping address for the order. |

| shipping_city | VARCHAR(100)| NOT NULL | NO | | Shipping city. |

| shipping_state | VARCHAR(100)| NOT NULL | NO | | Shipping state/province. |

| shipping_zip_code| VARCHAR(20)| NOT NULL | NO | | Shipping zip/postal code. |

| shipping_country| VARCHAR(100)| NOT NULL | NO | | Shipping country. |

| payment_method | VARCHAR(50)| | YES | | Method used for payment (e.g., "Credit Card", "PayPal"). |

| payment_status | VARCHAR(50)| NOT NULL, CHECK (payment_status IN ('Pending', 'Paid', 'Failed', 'Refunded')) | NO | 'Pending' | Status of the payment. |

| tracking_number| `VARCHAR(10

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"+slugTitle(pn)+"

Built with PantheraHive BOS

) } export default App "); zip.file(folder+"src/index.css","*{margin:0;padding:0;box-sizing:border-box} body{font-family:system-ui,-apple-system,sans-serif;background:#f0f2f5;color:#1a1a2e} .app{min-height:100vh;display:flex;flex-direction:column} .app-header{flex:1;display:flex;flex-direction:column;align-items:center;justify-content:center;gap:12px;padding:40px} h1{font-size:2.5rem;font-weight:700} "); zip.file(folder+"src/App.css",""); zip.file(folder+"src/components/.gitkeep",""); zip.file(folder+"src/pages/.gitkeep",""); zip.file(folder+"src/hooks/.gitkeep",""); Object.keys(extracted).forEach(function(p){ var fp=p.startsWith("src/")?p:"src/"+p; zip.file(folder+fp,extracted[p]); }); zip.file(folder+"README.md","# "+slugTitle(pn)+" Generated by PantheraHive BOS. ## Setup ```bash npm install npm run dev ``` ## Build ```bash npm run build ``` ## Open in IDE Open the project folder in VS Code or WebStorm. "); zip.file(folder+".gitignore","node_modules/ dist/ .env .DS_Store *.local "); } /* --- Vue (Vite + Composition API + TypeScript) --- */ function buildVue(zip,folder,app,code,panelTxt){ var pn=pkgName(app); var C=cc(pn); var extracted=extractCode(panelTxt); zip.file(folder+"package.json",'{ "name": "'+pn+'", "version": "0.0.0", "type": "module", "scripts": { "dev": "vite", "build": "vue-tsc -b && vite build", "preview": "vite preview" }, "dependencies": { "vue": "^3.5.13", "vue-router": "^4.4.5", "pinia": "^2.3.0", "axios": "^1.7.9" }, "devDependencies": { "@vitejs/plugin-vue": "^5.2.1", "typescript": "~5.7.3", "vite": "^6.0.5", "vue-tsc": "^2.2.0" } } '); zip.file(folder+"vite.config.ts","import { defineConfig } from 'vite' import vue from '@vitejs/plugin-vue' import { resolve } from 'path' export default defineConfig({ plugins: [vue()], resolve: { alias: { '@': resolve(__dirname,'src') } } }) "); zip.file(folder+"tsconfig.json",'{"files":[],"references":[{"path":"./tsconfig.app.json"},{"path":"./tsconfig.node.json"}]} '); zip.file(folder+"tsconfig.app.json",'{ "compilerOptions":{ "target":"ES2020","useDefineForClassFields":true,"module":"ESNext","lib":["ES2020","DOM","DOM.Iterable"], "skipLibCheck":true,"moduleResolution":"bundler","allowImportingTsExtensions":true, "isolatedModules":true,"moduleDetection":"force","noEmit":true,"jsxImportSource":"vue", "strict":true,"paths":{"@/*":["./src/*"]} }, "include":["src/**/*.ts","src/**/*.d.ts","src/**/*.tsx","src/**/*.vue"] } '); zip.file(folder+"env.d.ts","/// "); zip.file(folder+"index.html"," "+slugTitle(pn)+"
"); var hasMain=Object.keys(extracted).some(function(k){return k==="src/main.ts"||k==="main.ts";}); if(!hasMain) zip.file(folder+"src/main.ts","import { createApp } from 'vue' import { createPinia } from 'pinia' import App from './App.vue' import './assets/main.css' const app = createApp(App) app.use(createPinia()) app.mount('#app') "); var hasApp=Object.keys(extracted).some(function(k){return k.indexOf("App.vue")>=0;}); if(!hasApp) zip.file(folder+"src/App.vue"," "); zip.file(folder+"src/assets/main.css","*{margin:0;padding:0;box-sizing:border-box}body{font-family:system-ui,sans-serif;background:#fff;color:#213547} "); zip.file(folder+"src/components/.gitkeep",""); zip.file(folder+"src/views/.gitkeep",""); zip.file(folder+"src/stores/.gitkeep",""); Object.keys(extracted).forEach(function(p){ var fp=p.startsWith("src/")?p:"src/"+p; zip.file(folder+fp,extracted[p]); }); zip.file(folder+"README.md","# "+slugTitle(pn)+" Generated by PantheraHive BOS. ## Setup ```bash npm install npm run dev ``` ## Build ```bash npm run build ``` Open in VS Code or WebStorm. "); zip.file(folder+".gitignore","node_modules/ dist/ .env .DS_Store *.local "); } /* --- Angular (v19 standalone) --- */ function buildAngular(zip,folder,app,code,panelTxt){ var pn=pkgName(app); var C=cc(pn); var sel=pn.replace(/_/g,"-"); var extracted=extractCode(panelTxt); zip.file(folder+"package.json",'{ "name": "'+pn+'", "version": "0.0.0", "scripts": { "ng": "ng", "start": "ng serve", "build": "ng build", "test": "ng test" }, "dependencies": { "@angular/animations": "^19.0.0", "@angular/common": "^19.0.0", "@angular/compiler": "^19.0.0", "@angular/core": "^19.0.0", "@angular/forms": "^19.0.0", "@angular/platform-browser": "^19.0.0", "@angular/platform-browser-dynamic": "^19.0.0", "@angular/router": "^19.0.0", "rxjs": "~7.8.0", "tslib": "^2.3.0", "zone.js": "~0.15.0" }, "devDependencies": { "@angular-devkit/build-angular": "^19.0.0", "@angular/cli": "^19.0.0", "@angular/compiler-cli": "^19.0.0", "typescript": "~5.6.0" } } '); zip.file(folder+"angular.json",'{ "$schema": "./node_modules/@angular/cli/lib/config/schema.json", "version": 1, "newProjectRoot": "projects", "projects": { "'+pn+'": { "projectType": "application", "root": "", "sourceRoot": "src", "prefix": "app", "architect": { "build": { "builder": "@angular-devkit/build-angular:application", "options": { "outputPath": "dist/'+pn+'", "index": "src/index.html", "browser": "src/main.ts", "tsConfig": "tsconfig.app.json", "styles": ["src/styles.css"], "scripts": [] } }, "serve": {"builder":"@angular-devkit/build-angular:dev-server","configurations":{"production":{"buildTarget":"'+pn+':build:production"},"development":{"buildTarget":"'+pn+':build:development"}},"defaultConfiguration":"development"} } } } } '); zip.file(folder+"tsconfig.json",'{ "compileOnSave": false, "compilerOptions": {"baseUrl":"./","outDir":"./dist/out-tsc","forceConsistentCasingInFileNames":true,"strict":true,"noImplicitOverride":true,"noPropertyAccessFromIndexSignature":true,"noImplicitReturns":true,"noFallthroughCasesInSwitch":true,"paths":{"@/*":["src/*"]},"skipLibCheck":true,"esModuleInterop":true,"sourceMap":true,"declaration":false,"experimentalDecorators":true,"moduleResolution":"bundler","importHelpers":true,"target":"ES2022","module":"ES2022","useDefineForClassFields":false,"lib":["ES2022","dom"]}, "references":[{"path":"./tsconfig.app.json"}] } '); zip.file(folder+"tsconfig.app.json",'{ "extends":"./tsconfig.json", "compilerOptions":{"outDir":"./dist/out-tsc","types":[]}, "files":["src/main.ts"], "include":["src/**/*.d.ts"] } '); zip.file(folder+"src/index.html"," "+slugTitle(pn)+" "); zip.file(folder+"src/main.ts","import { bootstrapApplication } from '@angular/platform-browser'; import { appConfig } from './app/app.config'; import { AppComponent } from './app/app.component'; bootstrapApplication(AppComponent, appConfig) .catch(err => console.error(err)); "); zip.file(folder+"src/styles.css","* { margin: 0; padding: 0; box-sizing: border-box; } body { font-family: system-ui, -apple-system, sans-serif; background: #f9fafb; color: #111827; } "); var hasComp=Object.keys(extracted).some(function(k){return k.indexOf("app.component")>=0;}); if(!hasComp){ zip.file(folder+"src/app/app.component.ts","import { Component } from '@angular/core'; import { RouterOutlet } from '@angular/router'; @Component({ selector: 'app-root', standalone: true, imports: [RouterOutlet], templateUrl: './app.component.html', styleUrl: './app.component.css' }) export class AppComponent { title = '"+pn+"'; } "); zip.file(folder+"src/app/app.component.html","

"+slugTitle(pn)+"

Built with PantheraHive BOS

"); zip.file(folder+"src/app/app.component.css",".app-header{display:flex;flex-direction:column;align-items:center;justify-content:center;min-height:60vh;gap:16px}h1{font-size:2.5rem;font-weight:700;color:#6366f1} "); } zip.file(folder+"src/app/app.config.ts","import { ApplicationConfig, provideZoneChangeDetection } from '@angular/core'; import { provideRouter } from '@angular/router'; import { routes } from './app.routes'; export const appConfig: ApplicationConfig = { providers: [ provideZoneChangeDetection({ eventCoalescing: true }), provideRouter(routes) ] }; "); zip.file(folder+"src/app/app.routes.ts","import { Routes } from '@angular/router'; export const routes: Routes = []; "); Object.keys(extracted).forEach(function(p){ var fp=p.startsWith("src/")?p:"src/"+p; zip.file(folder+fp,extracted[p]); }); zip.file(folder+"README.md","# "+slugTitle(pn)+" Generated by PantheraHive BOS. ## Setup ```bash npm install ng serve # or: npm start ``` ## Build ```bash ng build ``` Open in VS Code with Angular Language Service extension. "); zip.file(folder+".gitignore","node_modules/ dist/ .env .DS_Store *.local .angular/ "); } /* --- Python --- */ function buildPython(zip,folder,app,code){ var title=slugTitle(app); var pn=pkgName(app); var src=code.replace(/^```[w]* ?/m,"").replace(/ ?```$/m,"").trim(); var reqMap={"numpy":"numpy","pandas":"pandas","sklearn":"scikit-learn","tensorflow":"tensorflow","torch":"torch","flask":"flask","fastapi":"fastapi","uvicorn":"uvicorn","requests":"requests","sqlalchemy":"sqlalchemy","pydantic":"pydantic","dotenv":"python-dotenv","PIL":"Pillow","cv2":"opencv-python","matplotlib":"matplotlib","seaborn":"seaborn","scipy":"scipy"}; var reqs=[]; Object.keys(reqMap).forEach(function(k){if(src.indexOf("import "+k)>=0||src.indexOf("from "+k)>=0)reqs.push(reqMap[k]);}); var reqsTxt=reqs.length?reqs.join(" "):"# add dependencies here "; zip.file(folder+"main.py",src||"# "+title+" # Generated by PantheraHive BOS print(title+" loaded") "); zip.file(folder+"requirements.txt",reqsTxt); zip.file(folder+".env.example","# Environment variables "); zip.file(folder+"README.md","# "+title+" Generated by PantheraHive BOS. ## Setup ```bash python3 -m venv .venv source .venv/bin/activate pip install -r requirements.txt ``` ## Run ```bash python main.py ``` "); zip.file(folder+".gitignore",".venv/ __pycache__/ *.pyc .env .DS_Store "); } /* --- Node.js --- */ function buildNode(zip,folder,app,code){ var title=slugTitle(app); var pn=pkgName(app); var src=code.replace(/^```[w]* ?/m,"").replace(/ ?```$/m,"").trim(); var depMap={"mongoose":"^8.0.0","dotenv":"^16.4.5","axios":"^1.7.9","cors":"^2.8.5","bcryptjs":"^2.4.3","jsonwebtoken":"^9.0.2","socket.io":"^4.7.4","uuid":"^9.0.1","zod":"^3.22.4","express":"^4.18.2"}; var deps={}; Object.keys(depMap).forEach(function(k){if(src.indexOf(k)>=0)deps[k]=depMap[k];}); if(!deps["express"])deps["express"]="^4.18.2"; var pkgJson=JSON.stringify({"name":pn,"version":"1.0.0","main":"src/index.js","scripts":{"start":"node src/index.js","dev":"nodemon src/index.js"},"dependencies":deps,"devDependencies":{"nodemon":"^3.0.3"}},null,2)+" "; zip.file(folder+"package.json",pkgJson); var fallback="const express=require("express"); const app=express(); app.use(express.json()); app.get("/",(req,res)=>{ res.json({message:""+title+" API"}); }); const PORT=process.env.PORT||3000; app.listen(PORT,()=>console.log("Server on port "+PORT)); "; zip.file(folder+"src/index.js",src||fallback); zip.file(folder+".env.example","PORT=3000 "); zip.file(folder+".gitignore","node_modules/ .env .DS_Store "); zip.file(folder+"README.md","# "+title+" Generated by PantheraHive BOS. ## Setup ```bash npm install ``` ## Run ```bash npm run dev ``` "); } /* --- Vanilla HTML --- */ function buildVanillaHtml(zip,folder,app,code){ var title=slugTitle(app); var isFullDoc=code.trim().toLowerCase().indexOf("=0||code.trim().toLowerCase().indexOf("=0; var indexHtml=isFullDoc?code:" "+title+" "+code+" "; zip.file(folder+"index.html",indexHtml); zip.file(folder+"style.css","/* "+title+" — styles */ *{margin:0;padding:0;box-sizing:border-box} body{font-family:system-ui,-apple-system,sans-serif;background:#fff;color:#1a1a2e} "); zip.file(folder+"script.js","/* "+title+" — scripts */ "); zip.file(folder+"assets/.gitkeep",""); zip.file(folder+"README.md","# "+title+" Generated by PantheraHive BOS. ## Open Double-click `index.html` in your browser. Or serve locally: ```bash npx serve . # or python3 -m http.server 3000 ``` "); zip.file(folder+".gitignore",".DS_Store node_modules/ .env "); } /* ===== MAIN ===== */ var sc=document.createElement("script"); sc.src="https://cdnjs.cloudflare.com/ajax/libs/jszip/3.10.1/jszip.min.js"; sc.onerror=function(){ if(lbl)lbl.textContent="Download ZIP"; alert("JSZip load failed — check connection."); }; sc.onload=function(){ var zip=new JSZip(); var base=(_phFname||"output").replace(/.[^.]+$/,""); var app=base.toLowerCase().replace(/[^a-z0-9]+/g,"_").replace(/^_+|_+$/g,"")||"my_app"; var folder=app+"/"; var vc=document.getElementById("panel-content"); var panelTxt=vc?(vc.innerText||vc.textContent||""):""; var lang=detectLang(_phCode,panelTxt); if(_phIsHtml){ buildVanillaHtml(zip,folder,app,_phCode); } else if(lang==="flutter"){ buildFlutter(zip,folder,app,_phCode,panelTxt); } else if(lang==="react-native"){ buildReactNative(zip,folder,app,_phCode,panelTxt); } else if(lang==="swift"){ buildSwift(zip,folder,app,_phCode,panelTxt); } else if(lang==="kotlin"){ buildKotlin(zip,folder,app,_phCode,panelTxt); } else if(lang==="react"){ buildReact(zip,folder,app,_phCode,panelTxt); } else if(lang==="vue"){ buildVue(zip,folder,app,_phCode,panelTxt); } else if(lang==="angular"){ buildAngular(zip,folder,app,_phCode,panelTxt); } else if(lang==="python"){ buildPython(zip,folder,app,_phCode); } else if(lang==="node"){ buildNode(zip,folder,app,_phCode); } else { /* Document/content workflow */ var title=app.replace(/_/g," "); var md=_phAll||_phCode||panelTxt||"No content"; zip.file(folder+app+".md",md); var h=""+title+""; h+="

"+title+"

"; var hc=md.replace(/&/g,"&").replace(//g,">"); hc=hc.replace(/^### (.+)$/gm,"

$1

"); hc=hc.replace(/^## (.+)$/gm,"

$1

"); hc=hc.replace(/^# (.+)$/gm,"

$1

"); hc=hc.replace(/**(.+?)**/g,"$1"); hc=hc.replace(/ {2,}/g,"

"); h+="

"+hc+"

Generated by PantheraHive BOS
"; zip.file(folder+app+".html",h); zip.file(folder+"README.md","# "+title+" Generated by PantheraHive BOS. Files: - "+app+".md (Markdown) - "+app+".html (styled HTML) "); } zip.generateAsync({type:"blob"}).then(function(blob){ var a=document.createElement("a"); a.href=URL.createObjectURL(blob); a.download=app+".zip"; a.click(); URL.revokeObjectURL(a.href); if(lbl)lbl.textContent="Download ZIP"; }); }; document.head.appendChild(sc); }function phShare(){navigator.clipboard.writeText(window.location.href).then(function(){var el=document.getElementById("ph-share-lbl");if(el){el.textContent="Link copied!";setTimeout(function(){el.textContent="Copy share link";},2500);}});}function phEmbed(){var runId=window.location.pathname.split("/").pop().replace(".html","");var embedUrl="https://pantherahive.com/embed/"+runId;var code='';navigator.clipboard.writeText(code).then(function(){var el=document.getElementById("ph-embed-lbl");if(el){el.textContent="Embed code copied!";setTimeout(function(){el.textContent="Get Embed Code";},2500);}});}