quarto-cli VS Pluto.jl

Hello, I have a rather specific question.

I want to write a detailed tutorial (as HTML page) and a condensed version of it (as Reveal JS slides) from a single document.

I have found this suggestion[1] to specify the separate output file name for the slides in the header, and `quarto render myfile.qmd` will generate both.

Is there a way to include content (long form text, code, or images) that will only be exported in the HTML page but not in the slides (where space is more limited)?

[1] https://github.com/quarto-dev/quarto-cli/discussions/1751

❯ docker build -t cavo789/quarto . [+] Building 208.2s (13/13) FINISHED docker:default => [internal] load .dockerignore 0.0s => => transferring context: 2B 0.0s => [internal] load build definition from Dockerfile 0.0s => => transferring dockerfile: 2.08kB 0.0s => [internal] load metadata for docker.io/eddelbuettel/r2u:20.04 3.4s => CACHED [ 1/10] FROM docker.io/eddelbuettel/r2u:20.04@sha256:133b40653e0ad564d348f94ad72c753b97fb28941c072e69bb6e03c3b8d6c06e 0.0s => [ 2/10] RUN set -e -x && apt-get update && apt-get install -y --no-install-recommends pandoc pandoc-citeproc curl gdebi-core librsvg2-bin python3.8 47.6s => [ 3/10] RUN set -e -x && install.r shiny jsonlite ggplot2 htmltools remotes renv knitr rmarkdown quarto 27.2s => [ 4/10] RUN set -e -x && curl -o quarto-linux-amd64.deb -L https://github.com/quarto-dev/quarto-cli/releases/download/v1.4.529/quarto-1.4.529-linux-amd64.deb && gdebi - 12.1s => [ 5/10] RUN set -e -x && groupadd -g 1000 -o "quarto" && useradd -m -u 1000 -g 1000 -o -s /bin/bash "quarto" 0.5s => [ 6/10] RUN set -e -x && quarto install tool tinytex --update-path 23.0s => [ 7/10] RUN set -e -x && printf "\e[0;105m%s\e[0;0m\n" "Run tlmgr update" && ~/.TinyTeX/bin/x86_64-linux/tlmgr update --self --all && ~/.TinyTeX/bin/x86_64-linux/fm 77.9s => [ 8/10] RUN set -e -x && printf "\e[0;105m%s\e[0;0m\n" "Run tlmgr install for a few tinyText packages (needed for PDF conversion)" && ~/.TinyTeX/bin/x86_64-linux/tlmgr 11.7s => [ 9/10] RUN set -e -x && mkdir -p /input 0.5s => exporting to image 4.0s => => exporting layers 4.0s => => writing image sha256:fe1d20bd71a66eb574ba1f5b35c988ace57c2c30f93159caa4d5de2f8c490eb0 0.0s => => naming to docker.io/cavo789/quarto 0.0s What's Next? View summary of image vulnerabilities and recommendations → docker scout quickview

I had some trouble following this but I think what you're saying is the ` [@Bernhofer2021.02.23.432527]` tag isn't getting converted to the actual bib reference - is that right? I just copied this into my system and I could make that part work fine - using my own .bib file of course, and I used this csl which I copied locally. The one change I made to the setup was to put both the .bib and the .csl file in my working directory where the .qmd file is, and also as I commented on a different post of yours from the other day, I make sure there's no spaces in the path to my working directory (for either the folder names or the filenames). So for me, everything is in C:\Users\xxxx\workingdir - this is due to a known RStudio issue with spaces. Who knows if that's what you're running into or not.

You should ask in the Quarto discussion group on their GitHub. They are extremely reactive if you can give a MWE.

I thought that notebook based development and package based development were diametrically opposed in the past, but Pluto.jl notebooks have changed my mind about this.

A Pluto.jl notebook is a human readable Julia source file. The Pluto.jl package is itself developed via Pluto.jl notebooks.

https://github.com/fonsp/Pluto.jl

Also, the VSCode Julia plugin tooling has really expanded in functionality and usability for me in the past year. The integrated debugging took some work to setup, but is fast enough to drop into a local frame.

https://code.visualstudio.com/docs/languages/julia

Julia is the first language I have achieved full life cycle integration between exploratory code to sharable package. It even runs quite well on my Android. 2023 is the first year I was able to solve a differential equation or render a 3D surface from a calculated mesh with the hardware in my pocket.

Re Julia there is also pluto.jl that is another notebook-like environment for julia. It's been a few years since I played with it but it looked cool, for example it handles state differently so you don't get into the same messes as with ipython notebooks. https://plutojl.org/

For this, Notebooks are often used. Julia offers a uniquely nice and interactive Pluto notebook for the web https://github.com/fonsp/Pluto.jl

I believe this is what Pluto sets out to do for Julia.

I used it as part of the “Computational Thinking” with Julia course a year or two back. Even then the beta software was very good and some of the demos the Pluto dev showed were nothing short of amazing

https://plutojl.org/

I think what you want is Pluto!

I like how Pluto.jl handles this:

> Pluto offers an environment where changed code takes effect instantly and where deleted code leaves no trace. Unlike Jupyter or Matlab, there is no mutable workspace, but rather, an important guarantee:

> At any instant, the program state is completely described by the code you see.

[1] https://github.com/fonsp/Pluto.jl