Visualization | Raku for Prediction

In this blog post we demonstrate how to do “Literate programming” in Raku via (short) pipelines of Command Line Interface (CLI) scripts.

An alternative of this CLI-based process is to use Mathematica or Jupyter notebooks.

Presentation’s GitHub directory

Video recording

Steps and components

Here is a narration of the diagram above:

Write some text and code in a Markdown file
- Program visualizations with “JavaScript::D3”, [AAp2]
Weave the Markdown file (i.e. “run it”)
- Using “Text::CodeProcessing”, [AAp3]
If the woven file the does not have D3.js graphics go to 5
Convert the woven Markdown file into HTML
- Using “Markdown::Grammar”, [AAp4]
Examine results
Go to 1
- Or finish “fiddling with it”

The conversions

The we use the document “Cryptocurrencies-explorations.md” (with Raku code over cryptocurrencies data.)

If no D3.js graphics are specified then we can use the shell command:

file-code-chunks-eval Cryptocurrencies-explorations.md

If D3.js graphics are specified then we can use the shell command:

file-code-chunks-eval Cryptocurrencies-explorations.md && 
  from-markdown Cryptocurrencies-explorations_woven.md -t html -o out.html && 
  open out.html

Remark: It is instructive to examine “Cryptocurrencies-explorations_woven.md” and compare it with “Cryptocurrencies-explorations.md”.

Remark The code chunks with graphics (using “JavaScript::D3”) have to have the chunk option setting results=asis.

Remark The “JavaScript::D3” commands have to have the option settings format => 'html' and div-id => ....