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Binder Test notebooks

S2S-Future DragonStone

This repository contains a collection of Jupyter notebooks with examples of using the Fastscape software stack for landscape evolution modeling and topographic analysis.

These notebooks were developed by Jean Braun in the framework of the first training program (called DragonStone) of the S2S-Future ITN (Innovative Training Network) in January 2021.

More information concerning FastScape on this website:

How to run the notebooks?

Run in the cloud (Binder)

You can run the notebooks in your browser without installing anything thanks to binder. Just follow the link below or click on the "launch binder" badge above and it will launch remotely a new notebook server for you:

This service is for demo purpose only, do not rely on it for doing more serious work.

Install and run locally (Docker)

Docker images are built automatically for this repository. Those images provide the whole computing environment, pre-installed and pre-configured for running the notebooks. The only requirement is to have Docker installed on your machine. It is available on all platforms Linux/Windows/Mac and it can be installed from the Docker website or using one of your platform's package managers.

Run the command below in a terminal to first pull the latest image (note: the Docker application must be running, you might need to launch it first):

$ docker pull fastscape/s2s-future-dragonstone:latest

Then run the command below to start the Jupyterlab application from the Docker container. Replace dragonstone by any other name you want to give to your local container (optional). Also Replace /path/to/local-notebook-folder by the full path to the directory on your machine where you want to create/copy, edit and permanently store notebooks for this training course.

$ docker run \
    -it \
    --name dragonstone \
    -p 8888:8888 \
    -v /path/to/local-notebook-folder:/home/jovyan/my-local-folder \
    fastscape/s2s-future-dragonstone \
    jupyter lab --ip

You can then enter in your browser the url and token provided to start using the Jupyterlab application.

You may want to copy the notebooks folder in your local working folder mounted in the docker container as my-local-folder. Open a terminal in Jupyterlab and run the following command:

$ cp -R notebooks my-local-folder/

When you are done you can stop and remove the container:

$ docker stop dragonstone
$ docker rm dragonstone


The url I entered in my browser doesn't point to Jupyterlab

You may already have another application running on localhost using the port 8888. Try another port when running the docker run command above, e.g., using -p 8889:8888. You also need to change the port in the entered url accordingly (e.g., localhost:8889).

The url I entered in my browser gives a page asking for a token

Copy and paste the token given in the url. If the token is invalid, you may have another Jupyterlab application already running on your machine. Try using another port as described above.

Check Docker's documentation for additional command line help and options.

Install and run locally (Conda)

Assuming that you have git and conda installed, you can install all the packages required to run the notebooks in a new conda environment using the following commands:

$ git clone
$ cd s2s-future-dragonstone
$ conda env create -f environment.yml
$ conda activate s2s-future-dragonstone

You also need to install a few Jupyterlab extensions with the following command (this step won't be required anymore with Jupyterlab >= 3.x):

$ jupyter labextension install \
    @jupyter-widgets/jupyterlab-manager \
    @pyviz/jupyterlab_pyviz \
    dask-labextension \

Finally run the command below to start the Jupyterlab application. It should open a new tab in your browser.

$ jupyter lab

How to contribute?

Your contribution is welcome! Your can do so by reporting issues, suggesting new notebook examples or improvements to the current examples.

A few extra steps are required to prepare your contributions. You can first update the conda environment using the following command:

$ conda env update -n s2s-future-dragonstone --file environment-dev.yml 

This installs a few additional packages like pre-commit, which is used to ensure that all notebook cell outputs are cleared before adding or updating notebooks in this git repository. Run the command below to enable pre-commit (you only need to do this once):

$ pre-commit install

The script below is useful if you want to ensure that all notebooks are running without error:

$ python

This script (as well as a script to build the Docker image) is run each time you open or update a pull-request on GitHub.


S2S-Future DragonStone training program materials (Jupyter notebooks)