CS1302 Jupyter

This is the repository for running the CS1302 Jupyter Environment outside a jupyterhub server.

1. To run the notebooks with temporary storage, click

2. To run locally on your computer with permanent storage:

• Install docker.
• Run the docker in a terminal from a working directory of your choice.
  • For Mac/Linux shells:

  docker run --rm -p 10000:8888 -m 4g \
          -v "${PWD}":/home/jovyan \
          chungc/cs1302:v0.81 \
          start-notebook.sh --NotebookApp.token=''

  • For Windows PowerShell:

  docker run --rm -p 10000:8888 -m 4g `
          -v ${PWD}:/home/jovyan `
          chungc/cs1302:v0.5 `
          start-notebook.sh --NotebookApp.token=''  

  • It may take a couple minutes to run for the first time as it needs to download the docker image. Subsequent run should be fast.
  • Port 10000 specified by -p should be free for use. Otherwise, change it to a free port on your computer.
  • The maximum memory limit is set to be 4GB by -m. You should set an appropriate value according to the memory available on your computer.
• Pull the notebooks from this repo in a web browser:
  http://localhost:10000/git-pull?repo=https%3A%2F%2Fgit.luolix.top%2Fccha23%2Fcs1302&urlpath=lab%2Ftree%2Fcs1302&branch=main
  • You can work on the notebooks under the cs1302 subfolder. Clicking the above link again will automatically pull and merge changes from the repo, without overwritting your changes.
  • To finish, stop the notebook server by pressing Control-C in the terminal that runs the docker or close the terminal/PowerShell.
  • To restart, run the docker command again from the same working directory.

3. To run on Visual Studio Code locally

• Install Visual Studio Code and the extension Remote - Containers.
• Click View->Command Palette
• Enter Remote-Containers: Clone Repository in Container Volume.... There is also a command for using a Named Container Volume instead.
• Enter the repository url https://github.com/ccha23/cs1302jupyter.git
• You can work on the notebooks in the cs1302 subfolder and your files will be kept in a persistent docker volume.
• You can start a jupyter lab server and open it in a browser by opening a terminal (Control-Shift-`) and run

jupyter lab --NotebookApp.token=''

• For more details, see the vscode-remote-try-python repository.