domino-workspaces

What this skill does

# Domino Workspaces Skill

## Description
This skill helps users work with Domino Workspaces - interactive development environments for data science work including Jupyter notebooks, JupyterLab, VS Code, and RStudio.

## Activation
Activate this skill when users want to:
- Launch or configure a workspace in Domino
- Work with Jupyter notebooks, VS Code, or RStudio
- Configure workspace settings (hardware tier, environment, volumes)
- Understand workspace persistence and file management
- Use SSH to connect to remote workspaces
- Install packages in workspaces

## Workspace Types

### Available IDEs
Domino provides these default workspace types:
- **Jupyter Notebook**: Classic notebook interface
- **JupyterLab**: Modern Jupyter interface with file browser
- **VS Code**: Full-featured code editor with extensions
- **RStudio**: IDE for R development
- **Custom IDEs**: Can configure additional workspace types

## Launching a Workspace

### Via Domino UI
1. Navigate to your project
2. Click **Workspaces** in the navigation
3. Click **Launch Workspace**
4. Select:
   - **IDE**: Choose Jupyter, VS Code, RStudio, etc.
   - **Hardware Tier**: CPU/memory/GPU resources
   - **Compute Environment**: Docker environment with tools
   - **Volume Size**: Persistent storage (if needed)
5. Click **Launch**

### Via Python SDK
```python
from domino import Domino

domino = Domino("project-owner/project-name")

# Start a workspace
workspace = domino.workspace_start(
    environment_id="env-123",
    hardware_tier_name="small",
    workspace_type="JupyterLab"
)

print(f"Workspace ID: {workspace['workspaceId']}")
```

## File Persistence

### Persistent Directories
Work saved to these directories persists across workspace sessions:
- `/mnt/` - Project files (synced with Domino)
- `/mnt/data/` - Domino Datasets
- `/mnt/artifacts/` - Project artifacts
- `/mnt/imported/` - Imported data

### Home Directory Persistence
Domino 6.1+ supports home directory persistence:
- Installed packages persist across sessions
- User configurations (.bashrc, .vimrc) are retained
- Reduces workspace startup time

## Package Installation

### Temporary (Current Session)
```bash
# Python packages
pip install pandas numpy scikit-learn

# R packages
install.packages("tidyverse")
```

### Persistent (Via Environment)
Add to environment's Dockerfile instructions:
```dockerfile
RUN pip install pandas numpy scikit-learn
```

Or use requirements.txt in your project:
```text
pandas>=2.0.0
numpy>=1.24.0
scikit-learn>=1.3.0
```

## SSH Access to Workspaces

Domino 6.1+ allows SSH connections from local machines:

1. **Enable SSH** in workspace settings
2. **Get connection details** from running workspace
3. **Connect via SSH**:
```bash
ssh -i ~/.ssh/domino_key user@workspace-hostname
```

Benefits:
- Use local IDE (VS Code Remote, PyCharm)
- Access remote compute from local machine
- Browse files locally while computing remotely

## Git Integration in Workspaces

### Using Git
```bash
# Clone a repo in workspace
git clone https://github.com/user/repo.git

# Standard git workflow
git add .
git commit -m "Update model"
git push origin main
```

### Sync with Domino
Click **Sync** in the workspace UI to push changes back to Domino project.

## Workspace Operations

### Stop a Workspace
```python
domino.workspace_stop(workspace_id)
```

### Resume a Workspace
Stopped workspaces can be resumed to continue work.

### View Workspace Logs
Access logs for debugging through the Domino UI or API.

## Best Practices

1. **Save frequently**: Sync work to Domino regularly
2. **Use appropriate hardware**: Match resources to workload
3. **Clean up**: Stop workspaces when not in use to save resources
4. **Version control**: Use Git for code versioning
5. **Environment management**: Use Domino Environments for reproducibility

## Troubleshooting

### Workspace Won't Start
- Check hardware tier availability
- Verify environment builds successfully
- Check resource quotas

### Lost Work
- Check `/mnt/` directories for persisted files
- Review Domino project files
- Check Git history if using version control

### Slow Startup
- Use smaller base environments
- Enable package persistence
- Pre-install packages in environment Dockerfile

## Documentation Reference
- [Use Workspaces](https://docs.dominodatalab.com/en/latest/user_guide/867b72/use-workspaces/)
- [Launch a Workspace](https://docs.dominodatalab.com/en/latest/user_guide/e6e601/workspaces)
- [Start a Jupyter Workspace](https://docs.dominodatalab.com/en/latest/user_guide/93aef2/start-a-jupyter-workspace/)