Use a Dockerfile for your Binder repository#

Binder supports configuration files for package installation, environment specification, post-build shell scripts, and more. It should be possible to create the environment that you want without using a Dockerfile. For more information about the different environment configuration files that Binder can create, see How can I prepare a repository for Binder?.

However, in case you cannot meet all your needs with these configuration files, it is also possible to use a Dockerfile to define your environment. This is considered an advanced use case, and we cannot guarantee that the Dockerfile will work.

This guide will help you in preparing your Dockerfile so that it has the components needed to run JupyterHub, allowing it to work on Binder deployments.


We recommend against using a Dockerfile as a way to make your repository usable with binder. Use them as a last resort after all methods in How can I prepare a repository for Binder? have failed.


Binder’s requirements for Dockerfiles are in beta and subject to change. Dockerfiles may break on Binder from time to time during the beta period.

When should you use a Dockerfile?#

Below are a few use-cases where you might want to use a Dockerfile with Binder.

When you are building complex software#

Most Binder configurations can be achieved without a Dockerfile. Before resorting to a Dockerfile, we recommend trying to use postBuild commands for configuration. See the repo2docker documentation for examples.

When you’re using a language that is not directly supported#

Binder supports many languages, but not all of them. If your need to use a different language, it may be possible to accomplish this with a Dockerfile.

For a list of languages that Binder supports with configuration files, see the repo2docker documentation.


We welcome contributions to repo2docker to add support for new languages. If interested, please open an issue.

Preparing your Dockerfile#

For a Dockerfile to work on Binder, it must meet the following requirements:

  1. It must install a recent version of Jupyter Notebook and JupyterLab. This should be installed via pip with the notebook and jupyterlab packages. So in your dockerfile, you should have a command like:

    RUN python3 -m pip install --no-cache-dir notebook jupyterlab


    If you install the classic notebook interface but not JupyterLab, you must manually change your URLs from /lab to /tree as described in the user interface documentation. Otherwise, you might get a 404: Not Found error when launching your project on binder.

    If you would like to use the repository with an authenticated Binder you should also install the jupyterhub package.

    RUN pip install --no-cache-dir jupyterhub
  2. It must explicitly specify a tag in the image you source.

    When sourcing a pre-existing Docker image with FROM, a tag is required. The tag cannot be latest. Note that tag naming conventions differ between images, so we recommend using the SHA tag of the image.

    Here’s an example of a Dockerfile FROM statement that would work.

    FROM jupyter/scipy-notebook:cf6258237ff9

    The following examples would not work:

    FROM jupyter/scipy-notebook


    FROM jupyter/scipy-notebook:latest
  3. It must set up a user whose uid is 1000. It is bad practice to run processes in containers as root, and on binder we do not allow root container processes. If you are using an ubuntu or debian based container image, you can create a user easily with the following directives somewhere in your Dockerfile:

    ARG NB_USER=jovyan
    ARG NB_UID=1000
    ENV HOME /home/${NB_USER}
    RUN adduser --disabled-password \
        --gecos "Default user" \
        --uid ${NB_UID} \

    This is the user that will be running the JupyterLab process when your repo is launched with binder. So any files you would like to be writeable by the launched binder notebook should be owned by this user.

  4. It must copy its contents to the $HOME directory and change permissions.

    To make sure that your repository contents are available to users, you must copy all contents to $HOME and then make this folder owned by the user you created in step 3. If you used the snippet provided in step 3, you can accomplish this copying with the following snippet:

    # Make sure the contents of our repo are in ${HOME}
    COPY . ${HOME}
    USER root
    RUN chown -R ${NB_UID} ${HOME}

    This chown is required because Docker will be default set the owner to root, which would prevent users from editing files. Note that the repository should in general be clone with COPY; although RUN git clone ... is a valid command for the Dockerfile, it does not invalidate the build cache of mybinder. Thus, if available, the the cached repository will be used even after changes to the repository.

  5. It must accept command-line arguments. The Dockerfile will effectively be launched as:

    docker run <image> jupyter notebook --NotebookApp.default_url=/lab/ <arguments from the mybinder launcher>

    where {}<arguments ...> includes important information automatically set by the binder environment, such as the port and token.

    If your Dockerfile sets or inherits the Docker {}ENTRYPOINT instruction, the program specified as the {}ENTRYPOINT must {}exec the arguments passed by docker. Inherited Dockerfiles may unset the entrypoint with {}ENTRYPOINT [].

    For more information, and a shell wrapper example, please see the Dockerfile best practices: ENTRYPOINT documentation.

You can build and test your image locally like this.

  1. Try building your image.

    docker build -t my-image .
  2. Try starting a container from the image.

    docker run -it --rm -p 8888:8888 my-image jupyter notebook --NotebookApp.default_url=/lab/ --ip= --port=8888
  3. Inspect the container from terminal.

    Verify your user has an id of 1000 and ownership of files in the home folder.

    docker run -it --rm my-image bash
    # what username do i have?
    # what user id do i have?
    id -u
    # what is the current working directory?
    # who is the owner of the files in the users home directory?
    ls -alh ~

Ensuring reproducibility with Dockerfiles#

Ensuring that your Binder environment is reproducible requires extra considerations when using a Dockerfile. This section provides some guidelines for making sure your Binder environment does not change in unexpected ways.

As mentioned above, make sure that you source your Dockerfile from a tag of another image. This ensures that you will continue building off of the same image even if the image is updated to a new version.

Next, make sure that all packages installed with your Dockerfile are pinned to specific versions. You should do this with the image you are sourcing as well.