https://github.com/datalayer/desktop
ฮ ๐ฅ๏ธ Datalayer Destkop.
https://github.com/datalayer/desktop
ai data data-analysis data-science datalayer desktop electron
Last synced: 3 months ago
JSON representation
ฮ ๐ฅ๏ธ Datalayer Destkop.
- Host: GitHub
- URL: https://github.com/datalayer/desktop
- Owner: datalayer
- Created: 2025-09-02T15:48:51.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2025-10-04T07:44:15.000Z (4 months ago)
- Last Synced: 2025-10-04T08:23:27.173Z (4 months ago)
- Topics: ai, data, data-analysis, data-science, datalayer, desktop, electron
- Language: TypeScript
- Homepage: https://datalayer.ai
- Size: 1.76 MB
- Stars: 3
- Watchers: 0
- Forks: 0
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- Security: SECURITY.md
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README
[](https://datalayer.io)
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[](https://github.com/datalayer/desktop/actions/workflows/build.yml)
[](https://github.com/datalayer/desktop/actions/workflows/test.yml)
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[](https://app.netlify.com/sites/datalayer-desktop/deploys)
[](https://datalayer-desktop.netlify.app)
# ๐ฅ๏ธ Datalayer Desktop
A powerful desktop application for data science and machine learning, powered by Jupyter notebooks and cloud computing.
## โจ Features
### Core Capabilities
- ๐ **Jupyter Notebooks** - Full-featured notebook editing with live kernel execution
- ๐ **Lexical Documents** - Rich text editor with embedded Jupyter cells for narrative documentation
- ๐ **Spaces Library** - Browse and manage your notebooks and documents across Datalayer spaces
- โ๏ธ **Runtime Management** - Create, monitor, and terminate cloud computing runtimes
- ๐ **Environment Selection** - Choose from Python, R, Julia, and specialized ML environments
### Collaboration & Cloud
- โ๏ธ **Cloud Computing** - Access powerful cloud runtimes for your computations
- ๐ **Real-time Collaboration** - Work together on Lexical documents with live editing (beta)
- ๐ **Secure** - Enterprise-grade security with encrypted connections and token storage
- ๐พ **Auto-save** - Never lose your work with automatic cloud synchronization
## ๐ฅ Installation
### Download Pre-built Application
Download the latest version for your operating system:
- **macOS**: [Download .dmg](https://github.com/datalayer/desktop/releases/latest) (Universal - works on Intel & Apple Silicon)
- **Windows**: [Download .exe](https://github.com/datalayer/desktop/releases/latest)
- **Linux**: [Download .AppImage](https://github.com/datalayer/desktop/releases/latest)
### System Requirements
- **Operating System**: macOS 10.12+, Windows 10+, or Linux
- **Memory**: 4GB RAM minimum (8GB recommended)
- **Storage**: 500MB available space
- **Internet**: Required for cloud features
## ๐ Getting Started
1. **Download and Install** the application for your operating system
2. **Launch** Datalayer Desktop from your Applications folder or Start menu
3. **Sign In** with your GitHub account through Datalayer authentication
4. **Select an Environment** - Choose your preferred runtime environment (Python, AI/ML, etc.)
5. **Browse Spaces** - Access your notebooks and documents from the library
6. **Create or Open** a notebook or document to start working
7. **Create Runtimes** - Spin up cloud computing resources when needed for execution
## ๐ Documentation
- **User Guide**: [docs.datalayer.io](https://docs.datalayer.io)
- **API Documentation**: [datalayer-desktop.netlify.app](https://datalayer-desktop.netlify.app)
## ๐ค Community & Support
- **Issues**: [GitHub Issues](https://github.com/datalayer/desktop/issues)
- **Discussions**: [GitHub Discussions](https://github.com/datalayer/desktop/discussions)
- **Discord**: [Join our Discord](https://discord.gg/datalayer)
## ๐ง For Developers
If you want to contribute or build from source, please see:
- [DEVELOPMENT.md](DEVELOPMENT.md) - Development setup and architecture
- [CONTRIBUTING.md](CONTRIBUTING.md) - Contribution guidelines
- [RELEASE.md](RELEASE.md) - Release and packaging instructions
- [CLAUDE.md](CLAUDE.md) - AI assistant context and troubleshooting guide
### Testing (January 2025) ๐งช
A comprehensive test suite has been implemented with **40+ test assertions** covering:
- **Unit Tests**: Components, utilities, and stores
- **Integration Tests**: IPC communication and service integration
- **E2E Tests**: Full user flows with Playwright
**Quick Start**:
```bash
npm test # Run all tests
npm run test:watch # Watch mode for development
npm run test:coverage # Generate coverage report
npm run test:ui # Visual test runner
```
**Documentation**:
- [TESTING.md](TESTING.md) - Testing guide and quick start
**Coverage Goals**: 70%+ overall, 90%+ critical path
## ๐ License
This project is licensed under the BSD-3-Clause License - see the [LICENSE](LICENSE.txt) file for details.
## ๐ข About Datalayer
[Datalayer](https://datalayer.io) is an AI platform for data analysis, making advanced data science accessible to everyone.
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