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<!DOCTYPE html>
<html lang="" xml:lang="" xmlns="http://www.w3.org/1999/xhtml">
<head>
<meta charset="utf-8"/>
<meta content="pandoc" name="generator"/>
<meta content="width=device-width, initial-scale=1.0, user-scalable=yes" name="viewport"/>
<meta content="Detlef Groth" name="author"/>
<meta content="2023-01-12" name="dcterms.date"/>
<title>Tutorial for the Pandoc Tcl filter</title>
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<![endif]-->
</head>
<body>
<header id="title-block-header">
<h1 class="title">Tutorial for the Pandoc Tcl filter</h1>
<p class="author">Detlef Groth</p>
<p class="date">2023-01-12</p>
<div class="abstract">
<div class="abstract-title">Abstract</div>
<p>The Pantcl Pandoc Tcl filter allows you the embed Tcl code in code
blocks and short Tcl statements as well in the normal text of a Markdown
document. The code fragments will be executed dynamically and the output
of the Tcl commands can be shown in an extra code block or can replace
the code block as well. The pantcl application as well embeds other
filters written in Tcl for other tools like GraphViz dot, LateX etc.</p>
</div>
</header>
<nav id="TOC" role="doc-toc">
<ul>
<li><a href="#name" id="toc-name">Name</a></li>
<li><a href="#usage" id="toc-usage">Usage</a></li>
<li><a href="#installation" id="toc-installation">Installation</a></li>
<li><a href="#tcl-filter" id="toc-tcl-filter">Tcl filter</a>
<ul>
<li><a href="#code-chunk-attributes" id="toc-code-chunk-attributes">Code
chunk attributes</a></li>
<li><a href="#images" id="toc-images">Images</a></li>
</ul></li>
<li><a href="#other-filters" id="toc-other-filters">Other
filters</a></li>
<li><a href="#dot-file-filter" id="toc-dot-file-filter">Dot file
filter</a></li>
<li><a href="#tsvg-plugin" id="toc-tsvg-plugin">tsvg plugin</a></li>
<li><a href="#filter-for-math-tex" id="toc-filter-for-math-tex">Filter
for Math-Tex</a></li>
<li><a href="#pic-and-eqn-filters" id="toc-pic-and-eqn-filters">PIC and
EQN filters</a></li>
<li><a href="#pikchr-filter" id="toc-pikchr-filter">Pikchr
filter</a></li>
<li><a href="#rplot-filter" id="toc-rplot-filter">Rplot filter</a></li>
<li><a href="#lua-filters" id="toc-lua-filters">Lua filters</a></li>
<li><a href="#summary" id="toc-summary">Summary</a></li>
<li><a href="#documentation" id="toc-documentation">Documentation</a></li>
<li><a href="#links" id="toc-links">Links</a></li>
<li><a href="#todo" id="toc-todo">Todo</a></li>
<li><a href="#author" id="toc-author">Author</a></li>
<li><a href="#license" id="toc-license">License</a></li>
</ul>
</nav>
<hr/>
<center>
<p>Filters: <a href="lib/tclfilters/filter-abc.html">filter-abc</a> - <a href="lib/tclfilters/filter-cmd.html">filter-cmd</a> - <a href="lib/tclfilters/filter-dot.html">filter-dot</a> - <a href="lib/tclfilters/filter-eqn.html">filter-eqn</a> - <a href="lib/tclfilters/filter-mmd.html">filter-mmd</a> - <a href="lib/tclfilters/filter-mtex.html">filter-mtex</a> - <a href="lib/tclfilters/filter-pic.html">filter-pic</a> - <a href="lib/tclfilters/filter-pik.html">filter-pik</a> - <a href="lib/tclfilters/filter-pipe.html">filter-pipe</a> - <a href="lib/tclfilters/filter-puml.html">filter-puml</a> - <a href="lib/tclfilters/filter-rplot.html">filter-rplot</a> - <a href="lib/tclfilters/filter-sqlite.html">filter-sqlite</a> - <a href="lib/tclfilters/filter-tcrd.html">filter-tcrd</a> - <a href="lib/tclfilters/filter-tcl.html">filter-tcl</a> - <a href="lib/tclfilters/filter-tdot.html">filter-tdot</a> - <a href="lib/tclfilters/filter-tsvg.html">filter-tsvg</a> <br/></p>
Documentation: <a href="pantcl.html">Pantcl documentation</a> - <a href="pantcl-tutorial.html">Pantcl Tutorial</a> - <a href="README.html">Pantcl Readme</a> - <a href="lib/fview/filter-view.html">Pantcl GUI filter viewer</a>
</center>
<hr/>
<h2 id="name">Name</h2>
<p><em>Tutorial Pantcl Tcl filter for Pandoc</em> - Tcl based pandoc
filter to execute programming and other Markup code within Markdown
documents and use code results for documentation.</p>
<h2 id="usage">Usage</h2>
<ul>
<li>works as filter for pandoc or just standalone (then only conversion
to HTML or Markdown is possible)</li>
<li>embedded graphical user interface, see <a href="filter-view.html">filter-view.html</a></li>
<li>evaluation of Tcl and other programming language code with textual
Markup files like Markdown or Asciidoc and adding the results, figures,
tables etc from the code evaluation to a resulting document like HTML,
PDF, DOCX, Markdown etc</li>
<li>easy to extend, many filters for other programming languages like
(Python, Octave, R) are already embedded</li>
<li>filters for many graphical tools such as GraphViz, Pikchr, PlantUML,
mermaid, LaTeX like</li>
<li>generic filter for all type of terminal applications such as
LilyPond, C/C++ compilers etc. where examples are given</li>
<li>all tools and filters can be applied within a single document</li>
<li>can be used to extract and process embedded Markdown documentation
in source code of different programming languages, such as C/C++, Tcl,
Python, etc.</li>
<li>the packed Tcl script with these features has a size of just around
1Mb</li>
</ul>
<p>Here some call syntax examples:</p>
<pre><code> pandoc input.md -s --filter pantcl.bin -o output.html
# or using the Tcl script from the unpacked application (not recommended)
pandoc input.md -s --filter pantcl.tcl -o output.html
# code documentation tool for extracting Markdown based documentation
# and evaluating code within code chunks as in standard Markdown documents
pantcl.bin sourcefile.tcl sourcfile.html --css file.css -s
# the same but not using pandoc but the internal Markdown library
# only conversion to HTML is possible
pantcl.bin sourcefile.tcl sourcfile.html --css file.css --no-pandoc
# graphical user interface
# files must have filter name extensions like
# .abc, .dot, .eqn, .mmd, .pic, .pik etc
pantcl.bin --gui somefile </code></pre>
<h2 id="installation">Installation</h2>
<p>The easiest way to install the pantcl Tcl filter application is by
using the standalone executable from the Github repository <a href="https://github.com/mittelmark/pantcl/">https://github.com/mittelmark/pantcl</a>
Download this file, rename the binary to <code>pantcl.bin</code> or just
<code>pantcl</code> and make it executable and place it a directory
belonging to your PATH variable. Windows user should use a Bash like
environment like the Git-Bash to make files executable. The only
prerequisite the application has is a working Tcl installation. The
required Tcl libraries are all wrapped into the standalone
exectuable.</p>
<p>Alternatively the application can be installed by specifying the
correct path to the Tcl script in your pandoc command line call.
Programmers which like to add their own filters can as well download and
modify the filters or add new filters in the filter directory. The
direct link to the github repository folder is: <a href="https://downgit.github.io/#/home?url=https://github.com/mittelmark/pantcl/tree/master/">https://downgit.github.io/#/home?url=https://github.com/mittelmark/pantcl/tree/master/</a>
Just unpack the folder and make the Tcl script <code>pantcl.tcl</code>
executable. Your pandoc call should then point to this directory.</p>
<p>The filter requires the Tcl package <em>rl_json</em> which is
available from Github: <a href="https://github.com/RubyLane/rl_json">https://github.com/RubyLane/rl_json</a>.
The standalone application already contains precompiled binaries for
64bit Linu, Windows and Mac-OSX. Unix users should be able to install
the <em>rl_json</em> package via the standard configure/make pipeline. A
Linux binary, complied on a recent Fedora system is included in the
download link at the GitHub page as well to simplify the use of the
Pandoc filter. Windows users should install the <em>rl_json</em> package
via the Magicplats Tcl-Installer: <a href="https://www.magicsplat.com/tcl-installer/index.html">https://www.magicsplat.com/tcl-installer</a></p>
<h2 id="tcl-filter">Tcl filter</h2>
<p>Below some basic information about the Tcl filter, more examples are
given in the Pantcl filter documentation file here: <a href="pantcl.html">pantcl.html</a>.</p>
<p>Tcl code can be embedded either within single backtick marks where
the first backtick is immediately followed by the string
<code>tcl</code> and the Tcl code such as in the following example:</p>
<pre><code>The variable is now `tcl set x 5` or five times three is `tcl expr {3*5}`.
This document was processed using Tcl `tcl package provide Tcl`.</code></pre>
<p>Here the output:</p>
<p>The variable is now 5 or five times three is 15.</p>
<p>This document was processed using Tcl 8.6.13.</p>
<p>The results from the code execution will be directly embedded in the
text and will replace the Tcl code. Such inline statements should be
short and concise and should not break over several lines. Currently
single backtick statements must be within non-list environments
only.</p>
<p>Larger chunks of code can be placed within triple backticks such as
in the example below.</p>
<pre><code> ```{.tcl eval=true}
# please remove the spaces before these lines
# they are used to guard against code evaluation
set x 3
proc add {x y} {
return [expr {$x+$y}]
}
add $x 7
```</code></pre>
<p>In the code above a space was added to avoid confusing the pandoc
interpreter by nested triple tickmarks, remove those spaces in your
code.</p>
<p>And here the output:</p>
<pre class="tclinn"><code>set x 3
proc add {x y} {
return [expr {$x+$y}]
}
add $x 7</code></pre>
<pre class="tclout"><code>10</code></pre>
<p>Please note, that only the last statement is shown in code block
after the Tcl code. To show more output you can use the
<code>puts</code> command.</p>
<h3 id="code-chunk-attributes">Code chunk attributes</h3>
<p>Within the curly braces the following attributes are currently
supported:</p>
<ul>
<li><em>eval=false|true</em> - evaluate the Tcl code</li>
<li><em>results=show|hide</em> - show the output of the Tcl code
execution</li>
<li><em>echo=true|false</em> - show the Tcl code</li>
</ul>
<p>Please note, that since version 0.9.9 the default for the
<code>eval</code> option is <code>false</code> (0), so you should enable
this code evaluation manually for each code chunk by writing in the code
chunk options something like <code>eval=true</code> or in the YAML
header using <code>eval: 1</code> - here you can’t use true or
false.</p>
<p>Here an example for a YAML header:</p>
<pre><code>---
tcl:
eval: 1
--- </code></pre>
<p>Errors in the Tcl code will be usually trapped and the error info is
shown instead of the regular output.</p>
<h3 id="images">Images</h3>
<p>As Tcl has no standard library in the core to create graphics without
the Tk toolkit we will create a small object using a minimal object
oriented system which can be used to create svg files easily.</p>
<h4 id="thingy-svg-example">Thingy svg example</h4>
<pre class="tclinn"><code>;# the onliner OO system thingy see here
;# https://wiki.tcl-lang.org/page/Thingy%3A+a+one%2Dliner+OO+system
proc thingy name {
proc $name args "namespace eval $name \$args"
}
;# our object
thingy svg
;# some variables
svg set code "" ;# the svg code
svg set header {<?xml version="1.0" encoding="utf-8" standalone="yes"?>
<svg version="1.1" xmlns="http://www.w3.org/2000/svg" height="__HEIGHT__" width="__WIDTH__">}
svg set footer {</svg>}
svg set width 100
svg set height 100
;# lets look what variables are there
info vars svg::* </code></pre>
<pre class="tclout"><code>::svg::width ::svg::height ::svg::header ::svg::footer ::svg::code</code></pre>
<p>We now need a method <em>unknown</em> which catches all command on
the object and forward this to the tag creation method.</p>
<pre class="tclinn"><code>;# the actual tag svg creation method
svg proc tag {args} {
variable code
set tag [lindex $args 0]
set args [lrange $args 1 end]
set ret "\n<$tag"
foreach {key val} $args {
if {$val eq ""} {
append ret ">\n$key\n</$tag>\n"
break
} else {
append ret " $key=\"$val\""
}
}
if {$val ne ""} {
append ret " />\n"
}
append code $ret
}
;# any unknown should forward to the tag method
namespace eval svg {
namespace unknown svg::tag
}
; # write out the current svg code
svg proc write {filename} {
variable width
variable height
variable header
variable footer
variable code
set out [open $filename w 0600]
set head [regsub {__HEIGHT__} $header $height]
set head [regsub {__WIDTH__} $head $width]
puts $out $head
puts $out $code
puts $out $footer
close $out
}
;# what methods we have
info commands svg::*</code></pre>
<pre class="tclout"><code>::svg::tag ::svg::write</code></pre>
<p>Ok we are now ready to go: Let’s create the typical “Hello World!”
example, the first argument will be the tag every remaining pairs will
be the attribute and the value, remaining single arguments will be
placed within the tag as content:</p>
<pre class="tclinn"><code>svg circle cx 50 cy 50 r 45 stroke black stroke-width 2 fill salmon
svg text x 29 y 45 Hello
svg text x 27 y 65 World!
svg write images/hello-world.svg</code></pre>
<p>Let’s now display the image:</p>
<pre><code> </code></pre>
<p>Here the image displayed:</p>
<p><img src="data:image/svg+xml;base64,PD94bWwgdmVyc2lvbj0iMS4wIiBlbmNvZGluZz0idXRmLTgiIHN0YW5kYWxvbmU9InllcyI/PgogICAgPHN2ZyB2ZXJzaW9uPSIxLjEiIHhtbG5zPSJodHRwOi8vd3d3LnczLm9yZy8yMDAwL3N2ZyIgaGVpZ2h0PSIxMDAiIHdpZHRoPSIxMDAiPgoKPGNpcmNsZSBjeD0iNTAiIGN5PSI1MCIgcj0iNDUiIHN0cm9rZT0iYmxhY2siIHN0cm9rZS13aWR0aD0iMiIgZmlsbD0ic2FsbW9uIiAvPgoKPHRleHQgeD0iMjkiIHk9IjQ1Ij4KSGVsbG8KPC90ZXh0PgoKPHRleHQgeD0iMjciIHk9IjY1Ij4KV29ybGQhCjwvdGV4dD4KCjwvc3ZnPgo="/><!--URL:images/hello-world.svg--></p>
<p>Let’s now clean up the svg code:</p>
<pre class="tclinn"><code>svg set code ""</code></pre>
<p>We can now create an other image, let’s create a chessboard:</p>
<pre class="tclinn"><code>svg set width 420
svg set height 420
for {set i 0} {$i < 8} {incr i} {
if {[expr {$i % 2}] == 0} {
set cols [join [lrepeat 4 [list cornsilk burlywood]]]
} else {
set cols [join [lrepeat 4 [list burlywood cornsilk ]]]
}
for {set j 0} {$j < 8} {incr j} {
set x [expr {10+$i*50}]
set y [expr {10+$j*50}]
svg rect x $x y $y width 50 height 50 fill [lindex $cols $j] stroke-width 3
}
svg rect x 6 y 6 width 408 height 408 stroke sienna stroke-width 7 fill transparent
}
svg write images/chessboard.svg</code></pre>
<p><img src="data:image/svg+xml;base64,<?xml version="1.0" encoding="utf-8" standalone="yes"?>
    <svg version="1.1" xmlns="http://www.w3.org/2000/svg" height="420" width="420">

<rect x="10" y="10" width="50" height="50" fill="cornsilk" stroke-width="3" />

<rect x="10" y="60" width="50" height="50" fill="burlywood" stroke-width="3" />

<rect x="10" y="110" width="50" height="50" fill="cornsilk" stroke-width="3" />

<rect x="10" y="160" width="50" height="50" fill="burlywood" stroke-width="3" />

<rect x="10" y="210" width="50" height="50" fill="cornsilk" stroke-width="3" />

<rect x="10" y="260" width="50" height="50" fill="burlywood" stroke-width="3" />

<rect x="10" y="310" width="50" height="50" fill="cornsilk" stroke-width="3" />

<rect x="10" y="360" width="50" height="50" fill="burlywood" stroke-width="3" />

<rect x="6" y="6" width="408" height="408" stroke="sienna" stroke-width="7" fill="transparent" />

<rect x="60" y="10" width="50" height="50" fill="burlywood" stroke-width="3" />

<rect x="60" y="60" width="50" height="50" fill="cornsilk" stroke-width="3" />

<rect x="60" y="110" width="50" height="50" fill="burlywood" stroke-width="3" />

<rect x="60" y="160" width="50" height="50" fill="cornsilk" stroke-width="3" />

<rect x="60" y="210" width="50" height="50" fill="burlywood" stroke-width="3" />

<rect x="60" y="260" width="50" height="50" fill="cornsilk" stroke-width="3" />

<rect x="60" y="310" width="50" height="50" fill="burlywood" stroke-width="3" />

<rect x="60" y="360" width="50" height="50" fill="cornsilk" stroke-width="3" />

<rect x="6" y="6" width="408" height="408" stroke="sienna" stroke-width="7" fill="transparent" />

<rect x="110" y="10" width="50" height="50" fill="cornsilk" stroke-width="3" />

<rect x="110" y="60" width="50" height="50" fill="burlywood" stroke-width="3" />

<rect x="110" y="110" width="50" height="50" fill="cornsilk" stroke-width="3" />

<rect x="110" y="160" width="50" height="50" fill="burlywood" stroke-width="3" />

<rect x="110" y="210" width="50" height="50" fill="cornsilk" stroke-width="3" />

<rect x="110" y="260" width="50" height="50" fill="burlywood" stroke-width="3" />

<rect x="110" y="310" width="50" height="50" fill="cornsilk" stroke-width="3" />

<rect x="110" y="360" width="50" height="50" fill="burlywood" stroke-width="3" />

<rect x="6" y="6" width="408" height="408" stroke="sienna" stroke-width="7" fill="transparent" />

<rect x="160" y="10" width="50" height="50" fill="burlywood" stroke-width="3" />

<rect x="160" y="60" width="50" height="50" fill="cornsilk" stroke-width="3" />

<rect x="160" y="110" width="50" height="50" fill="burlywood" stroke-width="3" />

<rect x="160" y="160" width="50" height="50" fill="cornsilk" stroke-width="3" />

<rect x="160" y="210" width="50" height="50" fill="burlywood" stroke-width="3" />

<rect x="160" y="260" width="50" height="50" fill="cornsilk" stroke-width="3" />

<rect x="160" y="310" width="50" height="50" fill="burlywood" stroke-width="3" />

<rect x="160" y="360" width="50" height="50" fill="cornsilk" stroke-width="3" />

<rect x="6" y="6" width="408" height="408" stroke="sienna" stroke-width="7" fill="transparent" />

<rect x="210" y="10" width="50" height="50" fill="cornsilk" stroke-width="3" />

<rect x="210" y="60" width="50" height="50" fill="burlywood" stroke-width="3" />

<rect x="210" y="110" width="50" height="50" fill="cornsilk" stroke-width="3" />

<rect x="210" y="160" width="50" height="50" fill="burlywood" stroke-width="3" />

<rect x="210" y="210" width="50" height="50" fill="cornsilk" stroke-width="3" />

<rect x="210" y="260" width="50" height="50" fill="burlywood" stroke-width="3" />

<rect x="210" y="310" width="50" height="50" fill="cornsilk" stroke-width="3" />

<rect x="210" y="360" width="50" height="50" fill="burlywood" stroke-width="3" />

<rect x="6" y="6" width="408" height="408" stroke="sienna" stroke-width="7" fill="transparent" />

<rect x="260" y="10" width="50" height="50" fill="burlywood" stroke-width="3" />

<rect x="260" y="60" width="50" height="50" fill="cornsilk" stroke-width="3" />

<rect x="260" y="110" width="50" height="50" fill="burlywood" stroke-width="3" />

<rect x="260" y="160" width="50" height="50" fill="cornsilk" stroke-width="3" />

<rect x="260" y="210" width="50" height="50" fill="burlywood" stroke-width="3" />

<rect x="260" y="260" width="50" height="50" fill="cornsilk" stroke-width="3" />

<rect x="260" y="310" width="50" height="50" fill="burlywood" stroke-width="3" />

<rect x="260" y="360" width="50" height="50" fill="cornsilk" stroke-width="3" />

<rect x="6" y="6" width="408" height="408" stroke="sienna" stroke-width="7" fill="transparent" />

<rect x="310" y="10" width="50" height="50" fill="cornsilk" stroke-width="3" />

<rect x="310" y="60" width="50" height="50" fill="burlywood" stroke-width="3" />

<rect x="310" y="110" width="50" height="50" fill="cornsilk" stroke-width="3" />

<rect x="310" y="160" width="50" height="50" fill="burlywood" stroke-width="3" />

<rect x="310" y="210" width="50" height="50" fill="cornsilk" stroke-width="3" />

<rect x="310" y="260" width="50" height="50" fill="burlywood" stroke-width="3" />

<rect x="310" y="310" width="50" height="50" fill="cornsilk" stroke-width="3" />

<rect x="310" y="360" width="50" height="50" fill="burlywood" stroke-width="3" />

<rect x="6" y="6" width="408" height="408" stroke="sienna" stroke-width="7" fill="transparent" />

<rect x="360" y="10" width="50" height="50" fill="burlywood" stroke-width="3" />

<rect x="360" y="60" width="50" height="50" fill="cornsilk" stroke-width="3" />

<rect x="360" y="110" width="50" height="50" fill="burlywood" stroke-width="3" />

<rect x="360" y="160" width="50" height="50" fill="cornsilk" stroke-width="3" />

<rect x="360" y="210" width="50" height="50" fill="burlywood" stroke-width="3" />

<rect x="360" y="260" width="50" height="50" fill="cornsilk" stroke-width="3" />

<rect x="360" y="310" width="50" height="50" fill="burlywood" stroke-width="3" />

<rect x="360" y="360" width="50" height="50" fill="cornsilk" stroke-width="3" />

<rect x="6" y="6" width="408" height="408" stroke="sienna" stroke-width="7" fill="transparent" />

</svg>
"/><!--URL:images/chessboard.svg--></p>
<p>Great! Let’s now illustrate a few more basic shapes. We will follow
the examples at <a href="https://developer.mozilla.org/en-US/docs/Web/SVG/Tutorial/Basic_Shapes">https://developer.mozilla.org/en-US/docs/Web/SVG/Tutorial/Basic_Shapes</a></p>
<p>But first let’s rewrite the <code>svg tag</code> function so that we
can as well take a list of attributes.</p>
<pre class="tclinn"><code>svg proc tag {args} {
variable code
set tag [lindex $args 0]
set args [lrange $args 1 end]
set ret "\n<$tag"
# new check if attr="val" syntax
if {[regexp {=} [lindex $args 0]]} {
set nargs [list]
foreach kval $args {
set idx [string first = $kval]
set key [string range $kval 0 $idx-1]
set val [string range $kval $idx+2 end-1]
lappend nargs $key
lappend nargs $val
}
set args $nargs
}
# end of new check
foreach {key val} $args {
if {$val eq ""} {
append ret ">\n$key\n</$tag>\n"
break
} else {
append ret " $key=\"$val\""
}
}
if {$val ne ""} {
append ret " />\n"
}
append code $ret
}</code></pre>
<p>With this redefinition of the tag method we can now very easily copy
the svg code from the website. We just have to remove the greater,
smaller and slash tag signs from the svg code. As arguments to functions
in Tcl are separated by spaces we have to protect attributes containing
spaces with curly braces for the last three shapes, the polyline, the
polygon and the path.</p>
<pre class="tclinn"><code>svg set code "" ;# cleanup chessboard
svg set width 200 ;# new size as on the webpage
svg set height 250
svg rect x="10" y="10" width="30" height="30" stroke="black" fill="transparent" stroke-width="5"
svg rect x="60" y="10" rx="10" ry="10" width="30" height="30" \
stroke="black" fill="transparent" stroke-width="5"
svg circle cx="25" cy="75" r="20" stroke="red" fill="transparent" stroke-width="5"
svg ellipse cx="75" cy="75" rx="20" ry="5" stroke="red" fill="transparent" stroke-width="5"
svg line x1="10" x2="50" y1="110" y2="150" stroke="orange" stroke-width="5"
svg polyline {points="60 110 65 120 70 115 75 130 80 125 85 140 90 135 95 150 100 145"} \
stroke="orange" fill="transparent" stroke-width="5"
svg polygon {points="50 160 55 180 70 180 60 190 65 205 50 195 35 205 40 190 30 180 45 180"} \
stroke="green" fill="transparent" stroke-width="5"
svg path {d="M20,230 Q40,205 50,230 T90,230"} fill="none" stroke="blue" stroke-width="5"
svg write images/basic-shapes.svg</code></pre>
<p><img src="data:image/svg+xml;base64,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"/><!--URL:images/basic-shapes.svg--></p>
<p>Ok, great basic shapes can be directly copied from svg code and with
a few modifications we can create valid Tcl code out of the svg code.
Please note, that from the code shown in this Readme the package
<em>tsvg</em> was derived which does not need this protecting of the
spaces within the attributes. See below the section about the
<em>tsvg</em> plugin for more details.</p>
<h4 id="code-chunk-attributes-for-svg-figures">Code chunk attributes for
svg figures</h4>
<p>Let’s introduce now a few code chunk attributes for figures as they
are known for instance in R.</p>
<p>Below an example:</p>
<pre><code> ```{.tcl fig=true fig.width=400 fig.height=400}
# some figure code
```</code></pre>
<p>This code should call some procedure figure with the arguments of a
basic filename, <em>fig.width</em>, <em>fig.height</em> and it should
return a filename with an extension like <code>.svg</code></p>
<p>Here an outline of such a function:</p>
<pre><code>proc figure {filename width height args} {
# parse args, get width, get height
# write file
# return filename with extension
}</code></pre>
<p>Ok, lets now implement our figure procedure for our svg:</p>
<pre class="tclinn"><code>proc figure {filename width height args} {
svg set width $width
svg set height $height
svg write images/$filename.svg
return $filename.svg
}</code></pre>
<p>Now in the next code chunk we create a new figure:</p>
<pre><code> ` ``{.tcl label=figsample fig=true width=80 height=80}
svg set code ""
svg rect x 0 y 0 width 80 height 80 fill cornsilk
svg rect x 10 y 10 width 60 height 60 fill salmon
` ``
</code></pre>
<p>Here the actual code (the space between the backticks was added to
avoid interpretation problems by pandoc):</p>
<pre class="tclinn"><code>svg set code ""
svg rect x 0 y 0 width 80 height 80 fill cornsilk
svg rect x 10 y 10 width 60 height 60 fill salmon</code></pre>
<p><img src="data:image/svg+xml;base64,PD94bWwgdmVyc2lvbj0iMS4wIiBlbmNvZGluZz0idXRmLTgiIHN0YW5kYWxvbmU9InllcyI/PgogICAgPHN2ZyB2ZXJzaW9uPSIxLjEiIHhtbG5zPSJodHRwOi8vd3d3LnczLm9yZy8yMDAwL3N2ZyIgaGVpZ2h0PSI4MCIgd2lkdGg9IjgwIj4KCjxyZWN0IHg9IjAiIHk9IjAiIHdpZHRoPSI4MCIgaGVpZ2h0PSI4MCIgZmlsbD0iY29ybnNpbGsiIC8+Cgo8cmVjdCB4PSIxMCIgeT0iMTAiIHdpZHRoPSI2MCIgaGVpZ2h0PSI2MCIgZmlsbD0ic2FsbW9uIiAvPgoKPC9zdmc+Cg=="/><!--URL:images/figsample.svg--></p>
<ul>
<li>TODO: autoembedding of figures by chunk number</li>
</ul>
<h2 id="other-filters">Other filters</h2>
<p>The <em>pantcl filter</em> supports as well generation of filters for
other tools and programming languages using the Tcl programming
language. The standalone application <em>pantcl.bin</em> comes with the
following filters:</p>
<table>
<colgroup>
<col style="width: 33%"/>
<col style="width: 33%"/>
<col style="width: 33%"/>
</colgroup>
<thead>
<tr class="header">
<th>filter</th>
<th>Tool</th>
<th>URL</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td>.abc</td>
<td>ABC music</td>
<td><a href="http://moinejf.free.fr/">http://moinejf.free.fr/</a></td>
</tr>
<tr class="even">
<td>.cmd</td>
<td>Bash scripts</td>
<td></td>
</tr>
<tr class="odd">
<td>.dot</td>
<td>dot/neato (GraphViz)</td>
<td><a href="https://graphviz.org/">https://graphviz.org/</a></td>
</tr>
<tr class="even">
<td>.emf</td>
<td>Jasspa MicroEmacs (me)</td>
<td><a href="http://www.jasspa.com/">http://www.jasspa.com</a></td>
</tr>
<tr class="odd">
<td>.eqn</td>
<td>eqn2graph (groff)</td>
<td><a href="https://www.gnu.org/software/groff/">https://www.gnu.org/software/groff/</a></td>
</tr>
<tr class="even">
<td>.mmd</td>
<td>mmdc (Mermaid-cli)</td>
<td><a href="https://www.npmjs.com/package/mermaid.cli">https://www.npmjs.com/package/mermaid.cli</a></td>
</tr>
<tr class="odd">
<td>.mtex</td>
<td>LaTex</td>
<td><a href="https://www.latex-project.org/">https://www.latex-project.org/</a></td>
</tr>
<tr class="even">
<td>.pic</td>
<td>pic2graph (groff)</td>
<td><a href="https://www.gnu.org/software/groff/">https://www.gnu.org/software/groff/</a></td>
</tr>
<tr class="odd">
<td>.pik</td>
<td>pikchr/fossil pikchr</td>
<td><a href="https://www.fossil-scm.org/home/doc/trunk/www/pikchr.md">https://www.fossil-scm.org/home/doc/trunk/www/pikchr.md</a></td>
</tr>
<tr class="even">
<td>.pipe</td>
<td>R, python, octave</td>
<td></td>
</tr>
<tr class="odd">
<td>.puml</td>
<td>plantuml</td>
<td><a href="https://plantuml.com/">https://plantuml.com/</a></td>
</tr>
<tr class="even">
<td>.rplot</td>
<td>Rscript</td>
<td><a href="https://www.r-project.org">https://www.r-project.org</a></td>
</tr>
<tr class="odd">
<td>.sqlite</td>
<td>sqlite3</td>
<td><a href="https://www.sqlite.org/index.html">https://www.sqlite.org</a></td>
</tr>
<tr class="even">
<td>.tcl</td>
<td>tclsh</td>
<td><a href="https://www.tcl.tk">https://www.tcl.tk</a></td>
</tr>
<tr class="odd">
<td>.tcrd</td>
<td>Tcl (chords for songs)</td>
<td></td>
</tr>
<tr class="even">
<td>.tdot</td>
<td>Tcl tdot package</td>
<td><a href="https://github.com/mittelmark/DGTcl">https://github.com/mittelmark/DGTcl</a></td>
</tr>
<tr class="odd">
<td>.tsvg</td>
<td>Tcl tsvg package</td>
<td><a href="https://github.com/mittelmark/DGTcl">https://github.com/mittelmark/DGTcl</a></td>
</tr>
</tbody>
</table>
<h2 id="dot-file-filter">Dot file filter</h2>
<p>Let’s finish our small tutorial with the implementation of a filter
for a command line application. Below you see the code for the GraphViz
dot application.</p>
<p>Here the code example (remove the space after the first backtick,
space was added to avoid interpretation):</p>
<pre><code>` ``{.dot label=digraph echo=true eval=true}
digraph G {
main -> parse -> execute;
main -> init [dir=none];
main -> cleanup;
execute -> make_string;
execute -> printf
init -> make_string;
main -> printf;
execute -> compare;
}
` ``</code></pre>
<p>Which will produce the following output:</p>
<pre class="dotinn"><code>digraph G {
main -> parse -> execute;
main -> init [dir=none];
main -> cleanup;
execute -> make_string;
execute -> printf
init -> make_string;
main -> printf;
execute -> compare;
}</code></pre>
<p><img src="data:image/svg+xml;base64,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"/><!--URL:/home/dgroth/workspace/pantcl/images/digraph.svg--></p>
<p>Using the chunk option <em>echo=false</em>, we can as well hide the
source code. If you would like to see the code you now have to consult
the Markdown file.</p>
<p><img src="data:image/svg+xml;base64,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"/><!--URL:/home/dgroth/workspace/pantcl/images/digraph2.svg--></p>
<p>To avoid automatic placement of figures you can as well set the
option include to false <em>include=false</em> and then create the usual
Markdown code for the figure where the basename is defined by a
<code>images</code> subfolder the chunk label.</p>
<pre><code>` ``{.dot label=digraph3 echo=false include=false eval=true}
digraph G {
main [shape=box,style=filled,fillcolor=".5 .8 1.0"] ;
main -> parse -> execute;
main -> init [style=dotted];
main -> cleanup;
execute -> make_string;
execute -> printf
edge [color="red"];
init -> make_string;
edge [dir="none"]; // no arrows
main -> printf;
execute -> compare;
}
` ``
</code></pre>
<p>This will produce the following:</p>
<p><img src="data:image/svg+xml;base64,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"/><!--URL:images/digraph3.svg--></p>
<p>OK, now you know what was the code to create the graphic above.</p>
<p>The dot filter supports as well the other command line applications
from the GraphViz toolbox. To switch for instance from the
<code>dot</code> command line application to the <code>neato</code>
application give the chunk argument <code>app=neato</code> and you can
enter neato code in your code chunk here an example:</p>
<pre><code>` ``{.dot label=neato app=neato eval=true}
graph G {
node [shape=box,style=filled,fillcolor=skyblue,
color=black,width=0.4,height=0.4];
n0 -- n1 -- n2 -- n3 -- n0 ;
}
` ``</code></pre>
<p>Which will produce this:</p>
<pre class="dotinn"><code>graph G {
node [shape=box,style=filled,fillcolor=skyblue,
color=black,width=0.4,height=0.4];
n0 -- n1 -- n2 -- n3 -- n0 ;
}</code></pre>
<p>You can try out as well the GraphViz layout engines yourself. Please
have a look at the GraphViz homepage at <a href="https://www.graphviz.org/docs/layouts/">https://www.graphviz.org/docs/layouts/</a>.</p>
<h2 id="tsvg-plugin">tsvg plugin</h2>
<p>The code shown above creating svg files using the thingy object was
as well saved as a plugin with some modifications and extensions. That
way you can include code creating svg files using the described syntax
above. Please not that the plugin object is named <code>tsvg</code>.
Here an example.</p>
<pre><code>` ``{.tsvg label=tsvg-hello-world results=hide echo=false eval=true}
tsvg circle cx 50 cy 50 r 45 stroke black stroke-width 2 fill salmon
tsvg text x 29 y 45 Hello
tsvg text x 26 y 65 World!
` ```</code></pre>
<p>Which will produce this:</p>
<pre class="tsvginn"><code>tsvg circle cx 50 cy 50 r 45 stroke black stroke-width 2 fill salmon
tsvg text x 29 y 45 Hello
tsvg text x 26 y 65 World!</code></pre>
<p><img src="data:image/svg+xml;base64,PD94bWwgdmVyc2lvbj0iMS4wIiBlbmNvZGluZz0idXRmLTgiIHN0YW5kYWxvbmU9InllcyI/PgogICAgPHN2ZyB2ZXJzaW9uPSIxLjEiIHhtbG5zPSJodHRwOi8vd3d3LnczLm9yZy8yMDAwL3N2ZyIgaGVpZ2h0PSIxMDAiIHdpZHRoPSIxMDAiPgoKPGNpcmNsZSBjeD0iNTAiIGN5PSI1MCIgcj0iNDUiIHN0cm9rZT0iYmxhY2siIHN0cm9rZS13aWR0aD0iMiIgZmlsbD0ic2FsbW9uIiAvPgoKPHRleHQgeD0iMjkiIHk9IjQ1Ij4KSGVsbG8KPC90ZXh0PgoKPHRleHQgeD0iMjYiIHk9IjY1Ij4KV29ybGQhCjwvdGV4dD4KCjwvc3ZnPgo="/><!--URL:/home/dgroth/workspace/pantcl/images/tsvg-hello-world.svg--></p>
<p>In contrast to the svg code developed above the <em>tsvg</em> plugin
allows you to send the attributes containing as well spaces as they are,
the <em>tag</em> method will clean up the lists arguments by using the
paired quotes. This greatly simplifies the copy and paste procedure for
existing svg examples, you in many cases just have to remove the leading
and trailing greater and lower signs. Here is an example using different
syntax types:</p>
<pre class="tsvginn"><code>tsvg set code ""
tsvg set width 180
tsvg set height 200
tsvg rect x 10 y 10 width 160 height 180 style "fill:#ddeeff;"
tsvg circle cx="130" cy="120" r="20" stroke="red" stroke-width="2" fill="salmon"
tsvg polyline points="0,40 40,40 40,80 80,80 80,120 120,120 120,160" \
style="fill:white;stroke:red;stroke-width:4"</code></pre>
<p><img src="data:image/svg+xml;base64,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"/><!--URL:/home/dgroth/workspace/pantcl/images/tsvg-polyline.svg--></p>
<p>For more information about the <em>tsvg</em> package visit the <a href="lib/tsvg/tsvg.html">tsvg manual page</a>.</p>
<h2 id="filter-for-math-tex">Filter for Math-Tex</h2>
<p>This filter requires a <em>LaTeX</em> installation and the
texlive-standalone package. The plugin uses in the background conversion
of a <em>LaTeX</em> formula using the <em>latex</em> command line
application and thereafter a conversion to png using the <em>dvipgn</em>
application which is part of the LaTeX installation. Please note that
currently only single line equations are supported:</p>
<p>Here two examples:</p>
<pre class="mtexinn"><code>$ E = m \times c^2 $</code></pre>
<p><img src="data:image/png;base64,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"/><!--URL:/home/dgroth/workspace/pantcl/images/mtex-7.png--></p>
<p>And here the second example:</p>
<pre class="mtexinn"><code>$ F(x) = \int^a_b \frac{1}{3}x^3 $</code></pre>
<p><img src="data:image/png;base64,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"/><!--URL:/home/dgroth/workspace/pantcl/images/mtex-8.png--></p>
<p>May be later version will support aligned sets of equations or
matrices.</p>
<h2 id="pic-and-eqn-filters">PIC and EQN filters</h2>
<p>The <em>groff</em> typesetting systems comes with the tools
<em>eqn2graph</em> which converts EQN equations into PNG graphics and
and <em>pic2graph</em> which converts diagram code written in the PIC
programming language into PNG graphics. Below are two examples, one for
each tool:</p>
<p>Here an example for the PIC language:</p>
<pre><code> ```{.pic ext=png eval=true}
circle "circle" rad 0.5 fill 0.3; arrow ;
ellipse "ellipse" wid 1.4 ht 1 fill 0.1 ; line;
box wid 1 ht 1 fill 0.05 "A";
spline;
box wid 0.4 ht 0.4 fill 0.05 "B";
arc;
box wid 0.2 ht 0.2 fill 0.05 "C";
```</code></pre>
<p>And here the output:</p>
<pre class="picinn"><code>circle "circle" rad 0.5 fill 0.3; arrow ;
ellipse "ellipse" wid 1.4 ht 1 fill 0.1 ; line;
box wid 1 ht 1 fill 0.05 "A";
spline;
box wid 0.4 ht 0.4 fill 0.05 "B";
arc;
box wid 0.2 ht 0.2 fill 0.05 "C";</code></pre>
<p><img 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<p>The complete code was:</p>
<pre><code> ```{.pic ext=png eval=true}
circle "circle" rad 0.5 fill 0.3; arrow ;
ellipse "ellipse" wid 1.4 ht 1 fill 0.1 ; line;
box wid 1 ht 1 fill 0.05 "A";
spline;
box wid 0.4 ht 0.4 fill 0.05 "B";
arc;
box wid 0.2 ht 0.2 fill 0.05 "C";
```</code></pre>
<p>And here an example for the EQN language:</p>
<p><img src="data:image/png;base64,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"/><!--URL:/home/dgroth/workspace/pantcl/images/eqn-10.png--></p>
<p>The code here was (the indentation of five spaces is just to avoid
interpretation), density 144 was used to make the equation smaller:</p>
<pre><code> ```{.eqn echo=false eval=true density=144}
x = {-b +- sqrt{b sup 2 - 4ac}} over 2a
```</code></pre>
<h2 id="pikchr-filter">Pikchr filter</h2>
<p>The PIC diagram language has a modern successor, the Pikchr diagram
language used on the Sqlite webpage to display syntax diagrams. The
homepage of the pikchr tool is at: <a href="https://pikchr.org">https://pikchr.org/</a>. The tool can be
compiled easily, but even easier you can as well download the
<em>fossil</em> application which has a subcommand <em>pikchr</em> which
allows you to create as well diagrams. The downloads of <em>fossil</em>
for various platforms can be found here <a href="https://www.fossil-scm.org/home/uv/download.html">https://www.fossil-scm.org/home/uv/download.html</a>.</p>
<p>If the <em>fossil</em> application is in your PATH ou can create
easily as well <em>pikchr</em> diagrams. Here an example:</p>
<pre class="pikchrinn"><code>box "box"
circle "circle" fill cornsilk at 1 right of previous
ellipse "ellipse" at 1 right of previous
oval "oval" at .8 below first box
cylinder "cylinder" at 1 right of previous
file "file" at 1 right of previous</code></pre>
<p><img src="data:image/svg+xml;base64,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"/><!--URL:/home/dgroth/workspace/pantcl/images/pik-11.svg--></p>
<p>The code for this diagram follows below:</p>
<pre><code>` ``{.pikchr app=fossil ext=pdf eval=true}
box "box"
circle "circle" fill cornsilk at 1 right of previous
ellipse "ellipse" at 1 right of previous
oval "oval" at .8 below first box
cylinder "cylinder" at 1 right of previous
file "file" at 1 right of previous
` ``</code></pre>
<p>Please note, that at least <em>fossil</em> in version 2.13 or higher
is required.</p>
<p>We can as well resize the image. In this case we have to create a
<em>png</em> extension. As conversion from svg to png is then required
we need a tool called cairosvg which can be installed as a Python
packagte using pip:</p>
<pre><code>pip3 install cairosvg --user</code></pre>
<p>Should do this. The advantage if using this tool is, that we beside
resizing we can as well create PDF’s for inclusion into LaTeX documents.
Here an example for a PNG image.</p>
<pre class="pikchrinn"><code>box "box"
circle "circle" fill cornsilk at 1 right of previous
ellipse "ellipse" at 1 right of previous
oval "oval" at .8 below first box
cylinder "cylinder" at 1 right of previous
file "file" at 1 right of previous</code></pre>
<p><img src="data:image/png;base64,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"/><!--URL:/home/dgroth/workspace/pantcl/images/fossil-sample.png--></p>
<p>Here is the code:</p>
<pre><code>` ``{.pikchr app=fossil ext=png width=500 height=300 eval=true}
` ``</code></pre>
<p>As you can see using the <code>ext=png</code> setting and the
<code>width</code> and <code>height</code> options, we can resize the
image.</p>
<h2 id="rplot-filter">Rplot filter</h2>
<p>The usual way to embed R code in Markdown is using the R-knitr
library and then use R to execute the code embedded within the
R-Markdown file. This type of execution is however not compatible with
pandoc as knitr modifies the code chunks without R-code as well. So it
is not easily possible to embed other filters in documents processed
with R/knitr first. Although the R-knitr command is useful if the main
focus is on R, it is however not favourable if you just would like to
add a few plots or execute a few statements. For a few simple plots you
can use the filter <code>.rplot</code> to embed them within your
document. Here an example.</p>
<pre class="rplotinn"><code>data(iris)
pairs(iris[,1:3],pch=19,col=as.numeric(iris$Species)+1)
x=1</code></pre>
<p><img src="data:image/png;base64,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"/><!--URL:/home/dgroth/workspace/pantcl/images/iris.png--></p>
<p>Here is the code:</p>
<pre><code>` ``{.rplot label=iris echo=true results="hide" width=800 height=600 eval=true}
data(iris)
pairs(iris[,1:3],pch=19,col=as.numeric(iris$Species)+1)
` ``</code></pre>
<p>And here just some code without a figure.</p>
<pre class="rplotinn"><code>print(head(iris))</code></pre>
<pre class="rplotout"><code> Sepal.Length Sepal.Width Petal.Length Petal.Width Species
1 5.1 3.5 1.4 0.2 setosa
2 4.9 3.0 1.4 0.2 setosa
3 4.7 3.2 1.3 0.2 setosa
4 4.6 3.1 1.5 0.2 setosa
5 5.0 3.6 1.4 0.2 setosa
6 5.4 3.9 1.7 0.4 setosa</code></pre>
<p>That is the code:</p>
<pre><code>` ``{.rplot fig=false eval=true}
print(head(iris))
` ``</code></pre>
<p>Session are as well retained, so you can use variables created in
code chunks before.</p>
<pre class="rplotinn"><code>print(x)</code></pre>
<pre class="rplotout"><code>[1] 1</code></pre>
<p>Here the code:</p>
<pre><code>` ``{.rplot fig=false eval=true}
print(x)
` ``</code></pre>
<p>In contrast to the R-knitr tool this filter will start for each chunk
a new process, so it is much slower then the R-knitr tool, so as I have
written above, it should be used mostly for Markdown documents with just
a few code chunks and with simple outputs. Thre is no support for
sophisticated features like nice tables etc..</p>
<h2 id="lua-filters">Lua filters</h2>
<p>Pandoc since version 2.0 has embedded support for Lua filters. To no
reinvent every filter again you should use Lua filters if they are
available. Below an example for a Lua filter:</p>
<pre><code> **strong** should be converted to smallcaps using the Lua filter _smallcaps.lua_!</code></pre>
<p><span class="smallcaps">strong</span> should be converted to
smallcaps using the Lua filter <em>smallcaps.lua</em>! To apply Lua
filters use the pandoc option
<code>--lua-filter=path/to/smallcaps.lua</code>.</p>
<p>For more details see the Pandoc documentation at <a href="https://pandoc.org/lua-filters.html">https://pandoc.org/lua-filters.html</a>
and for examples of Lua filter look at GitHub <a href="https://github.com/pandoc/lua-filters">https://github.com/pandoc/lua-filters</a>.</p>
<h2 id="summary">Summary</h2>
<p>In this Readme I explained on how to use the Tcl pandoc filter to
embed and process Tcl code during the creation of HTML or PDF documents.
The Tcl filter was generalized so that as well filters for other tools,
especially command line application can be easily programmed using the
Tcl programming language. Examples for a filter for the GraphViz tool
dot to create flowcharts and graphs, a package to create SVG images
using Tcl, the new <em>tsvg</em> package, a little renderer for single
TeX equations, filters for the PIC and EQN langauges and as well for the
Pikchr diagram tools are as well included in the pantcl.bin file. The
provided infrastructure has the advantage that Tcl programmers can stay
within their favourite programming language but still can use other nice
tools easily for their documentation. In case of new may be complex
things look for existing Lua filters. As Lua is embedded into Pandoc
have a look for an existing Lua filter to not reinvent the (filter)
wheel.</p>
<h2 id="documentation">Documentation</h2>
<p>The HTML version of this document was generated using the following
commandline:</p>
<pre><code>pantcl.bin pantcl-tutorial.md pantcl-tutorial.html --css mini.css -s
--toc --lua-filter=lib/tclfilters/smallcaps.lua
</code></pre>
<p>Please look at the source Markdown file to see which Markdown code
was the input.</p>
<h2 id="links">Links</h2>
<ul>
<li><a href="https://github.com/mittelmark/pantcl">Pantcl homepage at
GitHub</a></li>
<li><a href="https://wiki.tcl-lang.org/page/pandoc%2Dtcl%2Dfilter">Discussion
page for pantcl on the Tclers Wiki</a></li>
<li><a href="http://htmlpreview.github.io/?https://github.com/mittelmark/DGTcl/blob/master/pandoc-tcl-filter/lib/tsvg/tsvg.html">Documentation
to the tsvg package</a></li>
<li><a href="https://pandoc.org/filters.html">https://pandoc.org/filters.html</a>
- background on pandoc filters</li>
<li><a href="https://github.com/pandoc/lua-filters">Pandoc lua
filters</a></li>
<li><a href="https://github.com/mvhenderson/pandoc-filter-node">https://github.com/mvhenderson/pandoc-filter-node</a>
- pandoc filters using JavaScript and TypeScript</li>
<li><a href="https://pypi.org/project/panflute/">https://pypi.org/project/panflute/</a>
- pandoc filters in Python</li>
</ul>
<h2 id="todo">Todo</h2>
<ul>
<li>code block labels (label=chunkname) - done</li>
<li>code block figures (include=false fig=true) - done</li>
<li>regular filter infrastructure for Tcl support for for instance other
filters like .csv to include csv files .dot to include dot file graphics
etc. - done (examples for dot code and tsvg plugin)</li>
<li>Windows exe / starkit containing the rl_json library as well (adding
linux library)</li>
</ul>
<h2 id="author">Author</h2>
<p><span class="citation" data-cites="2021-2023">@2021-2023</span>:
Detlef Groth, Caputh-Schwielowsee, Germany</p>
<h2 id="license">License</h2>
<p>BSD license.</p>
</body>
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