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Initiation à Linux/Unix


Et si utiliser des lignes de commandes pouvait être facile et vous faire gagner en productivité ? Cette initiation vise à démystifier l'utilisation d'un terminal et du fonctionnement d'un ordinateur. Que vous travaillez sous Linux, Mac ou Windows, en apprenant l'utilisation d'une interface de ligne de commande Unix, vous serez en mesure de gagner en productivité lorsqu'il s'agit de gérer de nombreuses tâches telles que la gestion des fichiers et le contrôle des jobs. Cela vous ouvrira l'accès à de nombreux outils qui ne sont disponibles qu'en ligne de commande (ou de créer vos propres tâches automatisées). Ces bases seront essentielles si vous souhaitez par la suite travailler à distance sur des ordinateurs de haute performance (HPC). Les bases de programmation enseignées lors de ce cours sont des bases communes à tous les langages de programmation et pourront être mis à profit pour l'apprentissage d'autres langages.

Table of Contents

Foreword

The course itself lives https://isi.pages.ird.fr/isi-formation-unix/, where you can find all the relevant information.

Project layout

README.md               # General readme 
mkdocs.yml              # The configuration file for the site rendering.
conda_env.yml           # Conda env to build and test the site locally
docs/                   # material that will be publish with the static web site
    index.md            # The documentation homepage (Website Home page).
    pages/              # Folder dedicated to the course materials use by mkdocs for the website
        images          # Images used in the course materials in general
        xxx/            # Folder containning the course materials for one topic
            xxx.md      # Page taking about all or a part of the topic
            images/     # Images related to the topic
        ...    
    lectures/           # Folder dedicated to lectures (within docs to ease embedding within the course)
        README.md       # readme
        environment.yml # conda env to use for rendering the Rmarkdown lecture files
        template.css    # CSS used by all Rmarkdown lecture files
        Snakefile       # Automating rendering of all Rmarkdown lecture files
        xxx             # folder related to one lecture
            xxx.Rmd     # Lecture in Rmarkdown format
            xxx.pdf     # PDF rendering of Rmarkdown file
            xxx.html    # HTML rendering of Rmarkdown file
tutorials/              # Folder dedicated to tutorials
    xxx                 # folder related to one tutorial
Images                  # Images used in the README

## For collaborators-teachers and developers

This part is for collaborators-teachers and developers.

Modify content

When you are in the repository, add and/or modify your markdown tutorials in the docs directory. The arborescence of the website menu is to setup in the mkdocs.yml file

Mkdocs

Welcome to MkDocs

For full documentation visit mkdocs.org.
For full documentation about the material mkdocs theme.

Installation

Manual

As prerequisite you need python >=3.8 and pip.

Install Mkdocs:

pip install mkdocs

For the theme:
pip install mkdocs-material

For the extensions:
pip install pymdown-extensions

For the plugins:
pip install mkdocs-minify-plugin
pip install mkdocs-macros-plugin pip install mkdocs-include-markdown-plugin

Conda

Clone the repository and move in it.
Then install all dependencies using conda and the conda_env.yml shipped with this repo:

conda env create -f conda_env.yml

Activate the environment and you are good:

conda activate education

Testing and building the website

  • mkdocs serve - Start the live-reloading docs server, to test the site locally (http://127.0.0.1:8000/).

  • mkdocs gh-deploy - Deploys the site on github pages.

  • mkdocs build - Build the documentation site.

  • mkdocs new [dir-name] - Create a new project.

  • mkdocs -h - Print help message and exit.

License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Acknowledgment

The lecture is build ont top of a course made by i-Trop (The IRD Bioinformatics Platform) and Southgreen (website).
The training part is build on top of a course made by Jacques Dainat (git repo / website).