Access Jupyter notebook running on Docker container

Question

I created a docker image with python libraries and Jupyter. I start the container with the option -p 8888:8888 , to link ports between host and container. When I launch a Jupyter kernel inside the container, it is running on localhost:8888 (and does not find a browser). I used the command jupyter notebook

But from my host, what is the IP address I have to use to work with Jupyter in host's browser?

With the command ifconfig , I find eth0 , docker , wlan0 , lo ...

Thanks !

Answer 1

You need to run your notebook on 0.0.0.0 : jupyter notebook -i 0.0.0.0 . Running on localhost make it available only from inside the container.

Answer 2

Host machine: docker run -it -p 8888:8888 image:version

Inside the Container : jupyter notebook --ip 0.0.0.0 --no-browser --allow-root

Host machine access this url : localhost:8888/tree‌​

When you are logging in for the first time there will be a link displayed on the terminal to log on with a token.

Answer 3

The docker run command is mandatory to open a port for the container to allow the connection from a host browser, assigning the port to the docker container with -p, select your jupyter image from your docker images .

docker run -it -p 8888:8888 image:version

Inside the container launch the notebook assigning the port you opened:

jupyter notebook --ip 0.0.0.0 --port 8888 --no-browser --allow-root

Access the notebook through your desktops browser on http://localhost:8888 The notebook will prompt you for a token which was generated when you create the notebook.

Answer 4

To get the link to your Jupyter notebook server:

After your docker run command, a hyperlink should be automatically generated. It looks something like this: http://localhost:8888/?token=f3a8354eb82c92f5a12399fe1835bf8f31275f917928c8d2 :: /home/jovyan/work

If you want to get the link again later down the line, you can type docker exec -it <docker_container_name> jupyter notebook list .

Answer 5

The below is how I get it running on Windows 7 with docker toolbox.

If you are using docker toolbox, open up the Docker quickstart terminal, and note the IP here:

docker is configured to use the default machine with IP 192.168.99.100
For help getting started, check out the docs at https://docs.docker.com

Once you run the docker commands from the tensorflow installation website :

docker pull tensorflow/tensorflow                  # Download latest image
docker run -it -p 8888:8888 tensorflow/tensorflow  # Start a Jupyter notebook server

You will receive a message like this:

Copy/paste this URL into your browser when you connect for the first time,
to login with a token:
    http://127.0.0.1:8888/?token=d6e80acaf08e09853dc72f6b0f022b8225f94f

In the host, replace 127.0.0.1 with 192.168.99.100 and use the rest of that URL

Answer 6

您可以使用命令jupyter notebook --allow-root --ip[of your container]或使用选项--ip0.0.0.0授予对所有 ip 的访问权限。

Answer 7

As an alternative to building your own Docker image, you can also use the ML Workspace image. The ML Workspace is an open-source web IDE that combines Jupyter, VS Code, a Desktop GUI, and many other tools & libraries into one convenient Docker image. Deploying a single workspace instance is as simple as:

docker run -p 8080:8080 mltooling/ml-workspace:latest

All tools are accessible from the same port and integrated into the Jupyter UI. You can find further documentation here .

Answer 8

In the container you can run the following to make it available on your local machine (using your docker machine's ip address).

jupyter notebook --ip 0.0.0.0 --allow-root

You may not need to provide the --allow-root flag depending on your container's setup.

Answer 9

Check out the Torus project that Manifold open sourced recently. We wanted an easy way for our ML engineers to hit the ground running on new projects with a consistent development environment across the entire team. This Python cookiecutter will scaffold out a new project structure for you that includes a Dockerfile that uses a pre-baked ML dev image that we put in Docker Hub and a Docker Compose config that takes care of all the port forwarding for you. The config is written to pick an open port on your host machine to forward to the notebook server running on 8888 inside the container. No more hassle running multiple notebook servers on your machine! Check it out hopefully this is helpful!

Github repo: https://github.com/manifoldai/docker-cookiecutter-data-science

Why we built it (w/ demo): https://medium.com/manifold-ai/torus-a-toolkit-for-docker-first-data-science-bddcb4c97b52

Answer 10

docker run -i -t -p 8888:8888 continuumio/anaconda3 /bin/bash -c "/opt/conda/bin/conda install jupyter -y --quiet && mkdir /opt/notebooks && /opt/conda/bin/jupyter notebook --notebook-dir=/opt/notebooks --ip='*' --port=8888 --no-browser --allow-root"

i had to add --allow-root to the command and now its running

Answer 11

The Makefile below encapsulates the previous answers and ensures that jupyter and docker agree on the port. And if I just click/copy the link provided by jupyter, that solves port mismatch problems.

To use, just make jupyter or make jupyter PORT=xxxx from the proper folder. Then click the link in the jupyter output.

Remote Containers

If your container is on a remote host (say an AWS EC2), then you'll also need to set up an ssh tunnel with the correct port . For example, on the local machine:

ssh -N -f -L localhost:8888:localhost:8888 username@remote-host

But at least that's only one place I can manually mismatch ports.

Makefile

# Set your default jupyter port here. 
# Avoid 8888 if you run local notebooks on that!
PORT=8888
# Your app root in the container.
APP_DIR=/app
# The docker image to launch.  *** SET TO YOUR image:version! ***
APP_TAG=image:version

jupyter: ##
    ## Launch jupyter notebook from our container, mapping two folders
    ##    Local          Container       Notes
    ##    -----------------------------------------------------
    ##    ./data      -> /data           Put data here!
    ##    ./notebooks -> /notebooks      Find notebooks here!
    ##    -----------------------------------------------------
    ## Arg:  PORT - specify port [${PORT}]
    docker run \
        -p $(PORT):$(PORT) \
        -v $(PWD)/notebooks/:$(APP_DIR)/notebooks/ \
        -v $(PWD)/data:/data \
        $(APP_TAG) \
        jupyter notebook --ip 0.0.0.0 --port $(PORT) \
          --no-browser --allow-root

Answer 12

Go in the Docker and check cat /etc/jupyter/jupyter_notebook_config.py :

• You should see / add this line:

c.NotebookApp.allow_origin = 'https://colab.research.google.com'