Pastebin-Lite

A minimal, resilient Pastebin-like application built with Next.js and PostgreSQL.

Features

• Create Pastes: Share arbitrary text with syntax highlighting options.
• Constraints: Set Time-to-Live (TTL) and Maximum View Counts.
• Persistence: Data is stored reliably in PostgreSQL.
• Resilience: Handles high traffic and edge cases gracefully.
• Responsive Design: Modern UI that works on desktop and mobile.

Tech Stack

• Framework: Next.js (App Router)
• Language: TypeScript
• Database: PostgreSQL (via Prisma ORM)
• Validation: Zod
• Styling: Tailwind CSS

Project Structure

.
├── app/                  # Next.js App Router pages and layouts
│   ├── api/              # API routes
│   ├── p/[id]/           # Paste view page
│   └── page.tsx          # Main create paste page
├── components/           # Reusable UI components
├── lib/                  # Utilities, types, and database clients
├── prisma/               # Database schema and migrations
└── public/               # Static assets

Setup Instructions

Prerequisites

• Node.js (v18+)
• PostgreSQL installed and running

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/agnitha.git
   cd agnitha

2. Install dependencies:

   npm install

3. Configure Database:

   • Copy .env.example to .env (or create .env):

     cp .env.example .env

   • Set the DATABASE_URL in .env:

     DATABASE_URL="postgresql://user:password@localhost:5432/pastebin_lite?schema=public"

4. Run Migrations:

   npx prisma migrate dev --name init

5. Run the Development Server:

   npm run dev

6. Verify:

   • Visit http://localhost:3000 to create a paste.
   • Check /api/healthz for system status.

Testing

For automated testing with deterministic time:

• Set TEST_MODE=1 in your environment.
• Send requests with x-test-now-ms header to simulate time travel.

Persistence Decisions

This project uses PostgreSQL for persistence to ensure data durability and consistency across requests. Redis was considered for TTL but Postgres handles relational data and ACID compliance better for this use case, and TTL can be efficiently indexed.

Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

Distributed under the MIT License. See LICENSE for more information.