JSON-L Viewer

A high-performance, modern desktop application for viewing, searching, and analyzing large JSON and JSON-L (Newline Delimited JSON) files. Built with Tauri v2, Rust, and Svelte, it handles gigabytes of data with ease.

🚀 Features

• Streaming Architecture: Loads gigabytes of data instantly without blocking the UI.
• Virtual Scrolling: Efficiently renders millions of rows using virtualization.
• Auto-Column Detection: Automatically detects and flattens nested JSON structures into a readable table format.
• Smart Grouping: Visually groups related headers (e.g., user_name, user_id → USER) for better readability.
• Search & Filter: Real-time search functionality to quickly find specific records.
• Export Capabilities: Export your filtered view or entire datasets to CSV or Excel (.xlsx).
• Modern UI: Clean, native-feeling interface with Dark and Light (Zinc) themes.
• Cross-Platform: Runs natively on macOS, Windows, and Linux.

📸 Screenshots

🛠️ Tech Stack

• Frontend: Svelte 5, TailwindCSS, Lucide Icons.
• Backend: Rust (Tauri), Tokio (Async I/O), Serde.
• State Management: Svelte Stores.
• Build Tool: Vite.

� Download

You can download the latest version for macOS, Windows, and Linux from the Releases page:

👉 Download Binaries

�📦 Installation

This project uses pnpm (or npm) for the frontend and cargo for the backend.

Prerequisites

• Node.js (v18+)
• Rust (v1.70+)
• Tauri CLI

Development

1. Clone the repository:

   git clone https://github.com/icampana/jsonl-viewer.git
   cd jsonl-viewer
   

2. Install frontend dependencies:

   npm install
   

3. Run the application in development mode:

   npm run tauri dev
   

   This will start the Vite dev server and compile the Rust backend.

Building for Production

To create a release build for your operating system:

npm run tauri build

The build artifacts will be located in src-tauri/target/release/bundle/.

📖 Usage

1. Open File: Drag and drop a .json or .jsonl file, or use Cmd+O (File -> Open).
2. Open from URL: Use Cmd+Shift+O to load a file directly from a URL.
3. View Data: Scroll through the virtualized list. Columns are automatically generated from your data.
4. Search: Use the search bar efficiently filter rows based on content.
5. Export: Click "Export" in the menu (Cmd+E) or status bar to save your current view to Excel or CSV.

🧪 Test Data

You can test the application using the sample datasets provided by Microsoft Edge: JSON Dummy Data

Example URL to try: https://microsoftedge.github.io/Demos/json-dummy-data/1MB.json

Running on macOS

Since this app is not signed with an Apple Developer Certificate, you will see a warning when opening it for the first time ("App cannot be opened because the developer cannot be verified").

To bypass this:

1. Right-click (or Control-click) the app icon.
2. Select Open from the menu.
3. Click Open in the confirmation dialog.

Alternatively, you can remove the quarantine attribute via terminal:

xattr -cr /Applications/JSON-L\ Viewer.app

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

📄 License

This project is open source and available under the MIT License.