> For the complete documentation index, see [llms.txt](https://igb.mit.edu/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://igb.mit.edu/mini-courses/research-computing-on-engaging-with-vscode/connecting-to-engaging-via-ondemand/interactive-apps/jupyter-notebook.md).
# Jupyter Notebook
The Jupyter Notebook option allows you to run Jupyter Notebook on the cluster's compute nodes. Before starting Jupyter Notebook, you must configure the resource usage in the form below.
After filling out the form with the appropriate information, hit launch to queue launching Jupyter Notebook on the Engaging compute nodes.
While the job is in the queue, you'll see the following page, which contains basic information about the application you've launched, and will allow you to delete it from the queue.
Once the application has been launched, the page will update to include some basic settings and the "Connect to Jupyter" button. Pressing that will open Jupyter Notebook in a new browser tab.
Now, you can use Jupyter Notebook as normal. You can navigate to an existing Jupyter Notebook file on Engaging, create a new empty one, or upload one you have locally.
### Using Jupyter Notebook with custom Conda environments
If you have an existing Conda environment that you'd like to use in a Jupyter Notebook, you can make it available by installing Jupyter into your Conda environment and then registering that environment.
```bash
module load miniforge
conda activate MY_ENV
conda install jupyterlab
python -m ipykernel install --user --name $CONDA_DEFAULT_ENV
```
After you've run these set of commands, your environment will be listed when you open a new tab in Jupyter. For example, I've registered a Conda environment named `dreg` , and it is available in the list below:
