therobotacademy / Kaggle-Jupyter-R

Base Docker deployment of Kaggle environment for R, using Jupyter notebooks

Source: Utilizing the Kaggle Python Docker Container image

0. Create data folder

Docker container will map this folder.

mkdir data

1. Run the container based on kaggle/pythonimage:

docker run --restart always -v ${PWD}/data:/tmp/working -w=/tmp/working -p 8900:8888 --name kaggle-R \
   -d kaggle/rstats jupyter notebook --no-browser --ip="0.0.0.0" --notebook-dir=/tmp/working --allow-root

2. Access the log to get the http token for accessing Jupyter:

docker logs kaggle

For example:

http://640b804c545b:8888/?token=8e28bf1201d83f3f43521fba4b0cf382107781a4955ecf93&token=8e28bf1201d83f3f43521fba4b0cf382107781a4955ecf93

• Replace 640b804c545b with localhostor the IP of the machine where Kaggle image is running.
• Replace port 8888 (container) by 8900 (host)

Everything can be done with the bash script ./kaggle.sh

Using the Jupyter token

In the http line above:

token=8e28bf1201d83f3f43521fba4b0cf382107781a4955ecf93

Don't know why the next procedure does not set the password

So if you want to set a password for accessing Jupyter, after launching the container go to: http://HOST_IP:8890

Enter your token and change the password.

3. SSH into the container

docker exec -it kaggle bash