Computational Reproducibility with the shell, Git and Docker
This workshop provides an overview over tools for computational reproducibility in research. At the end of this workshop participants will be able to navigate via the shell and use it for version control with Git. They will know what types of projects require which forms of computing environments...
Keywords: scientific software, reproducibility, docker container, version control, shell
Resource type: slides
Computational Reproducibility with the shell, Git and Docker
https://osf.io/ar57z/
https://pan-training.eu/materials/computational-reproducibility-with-the-shell-git-and-docker
This workshop provides an overview over tools for computational reproducibility in research. At the end of this workshop participants will be able to navigate via the shell and use it for version control with Git. They will know what types of projects require which forms of computing environments and be able to set up a Docker container to run computations in a reproducible way.
scientific software, reproducibility, docker container, version control, shell
research data scientist
PhD students
researchers
scientists
Including Jupyter Notebooks in your Course
As a teacher, you can link a JupyterHub instance to your course that runs on our e-learning servers.The JupyterHub instance runs as a docker container that is launched when a student clicks on the link. The container will clone your chosen github repository where you can edit and store Jupyter...
Keywords: jupyter notebooks, docker container, moodle, e-teaching
Resource type: Moodle course, e-learning
Including Jupyter Notebooks in your Course
https://pan-learning.org/moodle/course/view.php?id=70
https://pan-training.eu/materials/including-jupyter-notebooks-in-your-course
As a teacher, you can link a JupyterHub instance to your course that runs on our e-learning servers.The JupyterHub instance runs as a docker container that is launched when a student clicks on the link. The container will clone your chosen github repository where you can edit and store Jupyter notebooks.Students will be able to open these Jupyter notebooks and execute them remotely.
Crucially students do not require Jupyter to be installed on their computers or have prior knowledge of python. Examples where this might be useful:
- Show students how to reduce and analyse experimental data themselves using python.
- Introduce students to python modules or software used in data reduction and analysis.
- Allow students to virtually explore large scale facility instruments. For example by using McStas (neutron instrument simulator).
- Teach students data modelling and simulation techniques that use python.
Requirements:
What the student will interact with must be in the form of a Jupyter notebook.
Your notebooks must be on a public github repository.
Note that the entire repository you provide will be cloned not just selected notebooks. However it does not have to be the master branch.
Our containers already include common scientific python modules such as numpy, matplotlib and ipython. In addition we have containers with the following software installed:
1. McStas, McXtrace, SCIPP, SasVIew
2. Crispy
3. SimEx
If you require a container with other software to be installed it is possible to have a custom container created. Please email admin@pan-learning.org for help.
Useful Links:
- [Jupyter notebooks](https://jupyter.org/)
- [What is a docker container](https://www.docker.com/resources/what-container)? (and the [wiki page](https://en.wikipedia.org/wiki/Docker_(software)))
- [Docker and Jupyterhub](https://hub.docker.com/r/jupyterhub/jupyterhub/#help-and-resources)
If you wish to include a link to a Jupyterhub container for your course.
Please fill the form: Information to set up your container
Once you have filled in the form you will receive an email to let you know the JupyterHub link is being set up and any further instructions that are required.
Please note it may take a few days to be up and running.
jupyter notebooks, docker container, moodle, e-teaching
