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Short Description
Jupyter Notebook Pytorch Stack
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<p align="center"><img width="40%" src="pytorch-logo-dark.png" /></p>

Jupyter Notebook Pytorch Stack

This image is based on Jupyter Notebook Scientific Python Stack.

What it Gives You

  • Jupyter Notebook 4.3.x
  • Conda Python 3.x and Python 2.7.x environments
  • pandas, matplotlib, scipy, seaborn, scikit-learn, scikit-image, sympy, cython, patsy, statsmodel, cloudpickle, dill, numba, bokeh, vincent, beautifulsoup, xlrd pre-installed
  • Unprivileged user jovyan (uid=1000, configurable, see options) in group users (gid=100) with ownership over /home/jovyan and /opt/conda
  • tini as the container entrypoint and as the default command
  • A script useful for running a single-user instance of the Notebook server, as required by JupyterHub
  • A script useful for running alternative commands in the container (e.g. ipython, jupyter kernelgateway, jupyter lab)
  • Options for HTTPS, password auth, and passwordless sudo

Basic Use

The following command starts a container with the Notebook server listening for HTTP connections on port 8888 with a randomly generated authentication token configured.

docker run -it --rm -p 8888:8888 stepankuzmin/pytorch-notebook

Take note of the authentication token included in the notebook startup log messages. Include it in the URL you visit to access the Notebook server or enter it in the Notebook login form.

Notebook Options

The Docker container executes a script script by default. The script handles the NB_UID and GRANT_SUDO features documented in the next section, and then executes the jupyter notebook.

You can pass Jupyter command line options through the script when launching the container. For example, to secure the Notebook server with a custom password hashed using IPython.lib.passwd() instead of the default token, run the following:

docker run -d -p 8888:8888 stepankuzmin/pytorch-notebook --NotebookApp.password='sha1:74ba40f8a388:c913541b7ee99d15d5ed31d4226bf7838f83a50e'

For example, to set the base URL of the notebook server, run the following:

docker run -d -p 8888:8888 stepankuzmin/pytorch-notebook --NotebookApp.base_url=/some/path

For example, to disable all authentication mechanisms (not a recommended practice):

docker run -d -p 8888:8888 stepankuzmin/pytorch-notebook --NotebookApp.token=''

You can sidestep the script and run your own commands in the container. See the Alternative Commands section later in this document for more information.

Docker Options

You may customize the execution of the Docker container and the Notebook server it contains with the following optional arguments.

  • -e GEN_CERT=yes - Generates a self-signed SSL certificate and configures Jupyter Notebook to use it to accept encrypted HTTPS connections.
  • -e NB_UID=1000 - Specify the uid of the jovyan user. Useful to mount host volumes with specific file ownership. For this option to take effect, you must run the container with --user root. (The script will su jovyan after adjusting the user id.)
  • -e GRANT_SUDO=yes - Gives the jovyan user passwordless sudo capability. Useful for installing OS packages. For this option to take effect, you must run the container with --user root. (The script will su jovyan after adding jovyan to sudoers.) You should only enable sudo if you trust the user or if the container is running on an isolated host.
  • -v /some/host/folder/for/work:/home/jovyan/work - Host mounts the default working directory on the host to preserve work even when the container is destroyed and recreated (e.g., during an upgrade).

SSL Certificates

You may mount SSL key and certificate files into a container and configure Jupyter Notebook to use them to accept HTTPS connections. For example, to mount a host folder containing a notebook.key and notebook.crt:

docker run -d -p 8888:8888 \
    -v /some/host/folder:/etc/ssl/notebook \
    stepankuzmin/pytorch-notebook \

Alternatively, you may mount a single PEM file containing both the key and certificate. For example:

docker run -d -p 8888:8888 \
    -v /some/host/folder/notebook.pem:/etc/ssl/notebook.pem \
    stepankuzmin/pytorch-notebook \

In either case, Jupyter Notebook expects the key and certificate to be a base64 encoded text file. The certificate file or PEM may contain one or more certificates (e.g., server, intermediate, and root).

For additional information about using SSL, see the following:

Conda Environments

The default Python 3.x Conda environment resides in /opt/conda. A second Python 2.x Conda environment exists in /opt/conda/envs/python2. You can switch to the python2 environment in a shell by entering the following:

source activate python2

You can return to the default environment with this command:

source deactivate

The commands jupyter, ipython, python, pip, easy_install, and conda (among others) are available in both environments. For convenience, you can install packages into either environment regardless of what environment is currently active using commands like the following:

# install a package into the python2 environment
pip2 install some-package
conda install -n python2 some-package

# install a package into the default (python 3.x) environment
pip3 install some-package
conda install -n python3 some-package

Alternative Commands

JupyterHub requires a single-user instance of the Jupyter Notebook server per user. To use this stack with JupyterHub and DockerSpawner, you must specify the container image name and override the default container run command in your

# Spawn user containers from this image
c.DockerSpawner.container_image = 'stepankuzmin/pytorch-notebook'

# Have the Spawner override the Docker run command
    'command': '/usr/local/bin/'

The script supports the same features as the default script (e.g., GRANT_SUDO), but allows you to specify an arbitrary command to execute. For example, to run the text-based ipython console in a container, do the following:

docker run -it --rm stepankuzmin/pytorch-notebook ipython

This script is particularly useful when you derive a new Dockerfile from this image and install additional Jupyter applications with subcommands like jupyter console, jupyter kernelgateway, and jupyter lab.


You can bypass the provided scripts and specify your an arbitrary start command. If you do, keep in mind that certain features documented above will not function (e.g., GRANT_SUDO).

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