How It Works

Dataset Viewer leverages a Tauri (Rust) backend with a React frontend for native performance and cross-platform compatibility. It employs chunked loading, virtual scrolling, and streaming processing to handle files exceeding 100GB without loading them entirely into memory. This approach ensures instant opening of large files and rapid, real-time search with highlighting.

Quick Start & Requirements

• Install: Download the latest release from https://github.com/stardustai/dataset-viewer/releases/latest.
• Prerequisites: No specific non-default prerequisites are mentioned beyond standard operating system requirements for Tauri applications (Windows, macOS, Linux).
• Setup Time: Not specified, but the focus on efficient loading suggests minimal setup time.

Highlighted Details

• Instant Large File Opening: Handles 100GB+ files with virtualized rendering.
• Millisecond Search: Real-time search with highlighting and fast positioning.
• Direct Archive Preview: Streams and previews contents of ZIP/TAR files without extraction.
• Multi-Source Data Access: Supports WebDAV, S3, local files, and HuggingFace datasets.
• Extensive File Type Support: Includes optimized rendering for Parquet, Excel, CSV, and text-based formats like JSON, YAML, and code files, with preview support for documents and media.

Maintenance & Community

The project is actively maintained, with clear channels for reporting bugs and requesting features via GitHub issues. The project acknowledges contributions from the Tauri, React, and Rust communities. Further community engagement details (e.g., Discord/Slack) are not provided in the README.

Licensing & Compatibility

• License: MIT License.
• Compatibility: The MIT license is permissive and generally compatible with commercial use and closed-source linking.

Limitations & Caveats

The README highlights that the entire codebase was generated by AI, which, while a notable feature, may imply potential areas for manual review or unexpected behavior in complex scenarios. Specific limitations regarding file type support or platform-specific issues are not detailed.