Data Science Terminal
Run Jupyter, Python, R, and data pipelines with file exploration and visualization. A complete data science terminal environment.
Why imux?
Keep your data scripts, Jupyter notebooks, file explorer, and results browser all in one organized workspace.
Key Features
- Multiple terminal sessions for different environments
- File explorer for data file navigation
- Browser surfaces for Jupyter and visualization dashboards
- Workspace persistence for long-running data jobs
- Git integration for experiment tracking
Getting Started
Set Up Your Data Environment
Open terminals for Python (with your preferred virtual environment), R, and any other tools you use. Each gets its own pane.
Add Jupyter and Dashboards
Open a browser surface for Jupyter Notebook. Add additional browser panes for Streamlit, R Shiny, or your visualization dashboards.
Explore Data Files
Use the file explorer to navigate datasets, browse CSV/Parquet files, and open scripts for editing — all within the same workspace.
Track with Git
imux automatically tracks changes to your scripts and notebooks. Use Git integration to version your experiments and collaborate.
FAQ
Does imux support Jupyter notebooks natively?
imux opens Jupyter in a browser surface and provides terminal access to run Jupyter server commands. You work with notebooks in the browser while managing your environment in the terminal.
Can I run long-running data jobs?
Yes. imux persists terminal sessions across app restarts. Long-running Python scripts, R jobs, or data pipelines continue running and you receive notifications when they complete.
How does imux handle large datasets?
The file explorer provides a quick way to navigate and inspect dataset files. Terminal tools like head, csvkit, or Python scripts handle the actual data processing at native speed.
Can I use imux with GPU-enabled remote servers?
Yes. Use imux's SSH remote workspace feature to connect to GPU servers. Run your training jobs in the terminal while monitoring GPU usage in another pane.