Coiled supports running hosted, sharable notebooks on through the coiled.create_notebook() interface. This enables you to run Jupyter sessions on the cloud with no local setup.


Coiled notebooks are currently experimental with new features under active development

When creating a Coiled notebook, you can specify:

  • Software to install for use in your Jupyter session

  • Any hardware resources to specify (e.g. amount of RAM, number of CPUs)

  • Local files to upload for use in the notebook (e.g. a local .ipynb notebook file)

  • Description of the notebook which will be rendered on

For example, below is a snippet which creates a “xgboost-demo” Coiled notebook:

import coiled

    conda={"channels": ["conda-forge"], "dependencies": ["xgboost", "dask"]},
    memory="8 GiB",
    description="Analyzes dataset with XGBoost",


Currently any directory structure for uploaded files will be removed and files will be placed in the working directory of the Jupyter session. For example, /path/to/notebook.ipynb will appear as notebook.ipynb in the Jupyter session.

After you’ve created a notebook, you can run the notebook by navigating to the “Notebooks” tab on the left sidebar of There you’ll find entries for notebooks you’ve created (see the screenshot below for an example), each of which has a button to launch a new Jupyter session for the corresponding notebook.


By default, any Coiled notebooks you create are publicly accessible to other Coiled users to promote sharing and collaborating. Private notebooks will be added in the future.


Using a custom image

By default, the command coiled.create_notebook() will use the Docker image coiled/notebook:latest to create your notebook, this image contains all the necessary dependencies and configuration for you to get started using notebooks.

If you want to use a custom image when creating a notebook, you will need to do some changes on how you create the notebook.

  • Make sure that you have jupyterlab installed

  • Add a custom command to start the notebook

For example, you could create your notebook following this snippet:

import coiled

    container="<your custom image>",
    conda=["jupyterlab", "ipywidgets"],
    command=("jupyter", "lab", "--allow-root", "--ip=", "--no-browser"),

Remember that you can still upload your files using the files keyword, alternatively you can copy those files into your custom image and they will be accessible when you start a notebook.


Even though you can access your files from your image, you will need to do some admin work if you want to save your work, since notebooks might be shutdown after some inactivity, making your changes unrecoverable.