This repository provides a NeuroLibre-compatible article template using MyST (Markedly Structured Text) for creating interactive scientific preprints.
https://events.neurolibre.org/mystical-article
This repository includes a GitHub Actions workflow that builds the MyST-formatted preprint and publishes it to GitHub Pages.
Tip
To enable this, you need to enable GitHub Pages in the repository settings (select GitHub Actions as the Build and deployment source).
Once you push your changes to the main branch, the GitHub Actions workflow will build the MyST-formatted preprint and publish it to your GitHub Pages.
Warning
The actions file (.github/workflows/deploy.yml) attempts to execute the executable content in this preprint. However, this doesn't always work smoothly in the GitHub Actions environment, as it requires starting a Jupyter Server and connecting to it. In other words, it may not generate the interactive figures as intended. Nevertheless, any changes you make to the narrative content will be reflected in the preprint.
The ultimate guide for authoring narrative and executable content in MyST documents is the MyST Guide.
Below is a decision tree guiding you through the process of preparing your living preprint before submitting it to the NeuroLibre for publication.
Note
This template includes executable content (simple Python code to generate interactive figures) and needs some data to be used as input. Let's take a look at how they are managed.
runtime.txtdeclarespython-3.10as the Python version.requirements.txtdeclares the Python packages that will be installed in your reproducible runtime environment.data_requirement.jsondeclares a download source (a simple csv file), which will be downloaded to a folder namedneurolibre-demo-dataset(project-name).- In your runtime environment the data will be mounted to
data/neurolibre-demo-dataset, relative to the base if your repository.
- In your runtime environment the data will be mounted to
Tip
Feel free to make small modifications to runtime dependencies and change your code to work with the provided data. However, if you need to work with a new data, let us know
The complete list of REES configuration files for different programming languages can be found here.
We provide a public Binder instance to help you create reproducible, interactive computing environments. Upon successfully building a Binder, a Docker image is pushed to our private registry, tagged with the commit hash of your repository.
NeuroLibre can use that Docker image over and over again to build new versions of your living preprint. So hold onto that commit hash and keep pushing commits to work on your narrative and executable content! Unless you need to install new dependencies or modify your input data, you don't need to build a new Binder.
RoboNeuro will be glad to build the latest version of your preprint (from the main branch) at each request!
Once you are happy with the current shape and form of your living print, submit it to NeuroLibre! Our team will start a technical screening to ensure that your preprint is ready for publication with the help of RoboNeuro on a GitHub issue.