Hello Quarto

share • collaborate • teach • reimagine

Pierre Navaro

pierre-navaro.quarto.pub/hello-quarto

artwork by allison horst

Publishing tools using Markdown

  • Static site generators: Jekyll, Hugo, Pelican.

  • Converters

    • Pandoc : a universal document converter
    • jupytext : Jupyter Notebooks as Markdown Documents, Julia, Python or R scripts

  • Slides

    • pandoc + beamer : use the presentation class for \(\LaTeX\)
    • remark : markdown-driven slideshow tool
    • RISE : Reveal.js - Jupyter/IPython Slideshow Extension

  • Julia

  • Transform a collection of notebooks to an html or pdf document.
  • Nice documentation https://jupyterbook.org,
  • utilizes Sphinx heavily under the hood
  • large community, many extensions and creators are friendly.
  • MyST syntax is really great.
  • High-quality printable pdf document
  • Rmd files could be used through jupytext (did not try)
  • This is the best alternative to quarto for books.
  • “Guide de Bonnes Pratiques sur la gestion des données de la Recherche” : pdf, html, repo.

The R Markdown

The rmarkdown package helps you create dynamic analysis documents that combine code, rendered output (such as figures), and prose. You bring your data, code, and ideas, and R Markdown renders your content into a polished document that can be used to:

  • Do data science interactively within the RStudio IDE,
  • Reproduce your analyses,
  • Collaborate and share code with others, and
  • Communicate your results with others. R Markdown documents can be rendered to many output formats including HTML documents, PDFs, Word files, slideshows, and more, allowing you to focus on the content while R Markdown takes care of your presentation.

The R Markdown ecosystem

Hex logos for various packages from the R Markdown ecosystem.

You can run Python or Julia code in an R Markdown document, but… you have to install R.

Quarto unifies and extends
the R Markdown ecosystem

Quarto unifies and extends
the R Markdown ecosystem


unifies for people who love R Markdown


extends for people who don’t know R Markdown

Quarto is a new, open-source,
scientific and technical
publishing system

Quarto is a new, open-source,
scientific and technical
publishing system

the goal is to make the process of creating
and collaborating dramatically better

A schematic representing the multi-language input (e.g. Python, R, Observable, Julia) and multi-format output (e.g. PDF, html, Word documents, and more) versatility of Quarto.

Quarto CLI orchestrates
each step of rendering

A schematic representing rendering of Quarto documents from .qmd, to knitr or jupyter, to plain text markdown, then converted by pandoc into any number of output types including html, PDF, or Word document.

Quarto enables contributing
from different tools

Screenshot of RStudio IDE

Screenshot of Jupyter Lab

Screenshot of GitHub IDE

Screenshot of VS Code IDE

Quarto makes moving between formats straightforward

Document

lesson-1.qmd

title: "Lesson 1"
format: html

Presentation

lesson-1.qmd

title: "Lesson 1"
format: revealjs

Website

_quarto.yml

project:
  type: website

website: 
  navbar: 
    left:
      - lesson-1.qmd

Rmd conversion with command line

  1. Install quarto
brew install quarto
  1. Convert the Rmd file
Rscript -e 'knitr::convert_chunk_header("document.Rmd", "document.qmd")'
  1. Improve your document
quarto preview document.qmd
  1. Render the final document
quarto render document.qmd
  1. Publish the document
quarto publish

Videos demos

Conclusion

  • Versatile, multi-languages, quarto is a great tool for publishing.
  • Quarto CLI is really a game changer.
  • Very well documented.
  • Publishing and hosting is really easy.
  • Very powerful syntax but the level of knowledge needed is still quite high.
  • Well integrated with RStudio and VSCode but can be used on the command line with a text editor which was difficult to do with the RMarkdown tools.

Examples

The examples I worked on to prepare this presentation

Journal of the French Statistical Society: computo.

  • A Python Package for Sampling from Copulae: clayton : html, pdf, repo.
  • Visualizing Data using t-SNE: a mock Computo contribution : html, repo.

Tutorials

References