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Alectryon

A library to process Coq and Lean 4 snippets embedded in text documents, showing goals and messages for each input sentence. Also a literate programming toolkit. The goal of Alectryon is to make it easy to write textbooks, blog posts, and other documents that mix interactive proofs and prose.

Alectryon is typically used in one of three ways:

  • As a library, through its Python API
  • As a Docutils/Sphinx extension, allowing you to include annotated snippets into your reStructuredText and Markdown documents. During compilation, Alectryon collects all .. coq:: code blocks, feeds their contents to Coq, and incorporates the resulting goals and responses into the final document.
  • As a standalone compiler, allowing you to include prose delimited by special (*| … |*) comments directly into your Coq source files (in the style of coqdoc). When invoked, Alectryon translates your Coq file into a reStructuredText document and compiles it using the standard reStructuredText toolchain.

For background information, check out the quickstart guide on the MIT PLV blog, the SLE2020 paper (open access) and its live examples, or the conference talk.

Alectryon is free software under a very permissive license. If you use it, please remember to cite it, and please let me know!

Some examples of use in the wild are linked at the bottom of this page. Please add your own work by submitting a PR!

Setup

To install from OPAM and PyPI:
opam install "coq-serapi>=8.10.0+0.7.0" (from the Coq OPAM archive)
python3 -m pip install alectryon

To install the latest version from Git, use python3 -m pip install git+https://github.com/cpitclaudel/alectryon.git. To install from a local clone, use python3 -m pip install ..

A note on dependencies: the serapi module only depends on the coq-serapi OPAM package. dominate is used in alectryon.html to generate HTML output, and pygments is used by the command-line application for syntax highlighting. reStructuredText support requires docutils (and optionally sphinx); Markdown support requires myst_parser (docs); Coqdoc support requires beautifulsoup4. Support for Coq versions follows SerAPI; Coq ≥ 8.10 works well and ≥ 8.12 works best.

Usage

As a standalone program

Recipes

Try these recipes in the recipes directory of this repository (for each task I listed two commands: a short one and a longer one making everything explicit):

Generate an interactive webpage from a literate Coq file with reST comments (Coqdoc style)
alectryon literate_coq.v
alectryon --frontend coq+rst --backend webpage literate_coq.v -o literate_coq.html
Generate an interactive webpage from a plain Coq file (Proof General style):
alectryon --frontend coq plain.v
alectryon --frontend coq --backend webpage plain.v -o plain.v.html
Generate an interactive webpage from a Coqdoc file (compatibility mode):
alectryon --frontend coqdoc coqdoc.v
alectryon --frontend coqdoc --backend webpage coqdoc.v -o coqdoc.html
Generate an interactive webpage from a reStructuredText document containing .. coq:: directives (coqrst style):
alectryon literate_reST.rst
alectryon --frontend rst --backend webpage literate_reST.rst -o literate_reST.html
Generate an interactive webpage from a Markdown document written in the MyST dialect, containing .. coq:: directives:
alectryon literate_MyST.md
alectryon --frontend md --backend webpage literate_MyST.md -o literate_MyST.html
Translate a reStructuredText document into a literate Coq file:
alectryon literate_reST.rst -o literate_reST.v
alectryon --frontend rst --backend coq+rst literate_reST.rst -o literate_reST.v
Translate a literate Coq file into a reStructuredText document:
alectryon literate_coq.v -o literate_coq.v.rst
alectryon --frontend coq+rst --backend rst literate_coq.v -o literate_coq.v.rst
Record goals and responses for fragments contained in a JSON source file:
alectryon fragments.v.json
alectryon --frontend coq.json --backend json fragments.json -o fragments.v.io.json
Record goals and responses and format them as HTML for fragments contained in a JSON source file:
alectryon fragments.v.json -o fragments.v.snippets.html
alectryon --frontend coq.json --backend snippets-html fragments.json -o fragments.v.snippets.html

Command-line interface

alectryon [-h] […]
          [--frontend {coq,coq+rst,coqdoc,json,md,rst}]
          [--backend {coq,coq+rst,json,latex,rst,snippets-html,snippets-latex,webpage,…}]
          input [input ...]

Use alectryon --help for full command line details.

  • Each input file can be .v (a Coq source file, optionally including reStructuredText in comments delimited by (*| … |*)), .json (a list of Coq fragments), .rst (a reStructuredText document including .. coq:: code blocks), or .md (a Markdown/MyST document including {coq} code blocks). Each input fragment is split into individual sentences, which are executed one by one (all code is run in a single Coq session).

  • One output file is written per input file. Each frontend supports a subset of all backends.

    • With --backend webpage (the default for most inputs), output is written as a standalone webpage named <input>.html (for coq+rst inputs) or <input>.v.html (for plain coq inputs).

    • With --backend snippets-html, output is written to <input>.snippets.html as a sequence of <pre class="alectryon-io"> blocks, separated by <!-- alectryon-block-end --> markers (there will be as many blocks as entries in the input list if input is a .json file).

    • With --backend json, output is written to <input>.io.json as a JSON-encoded list of Coq fragments (as many as in input if input is a .json file). Each fragment is a list of records, each with a _type and some type-specific fields. Here is an example:

      Input (minimal.json):
      ["Example xyz (H: False): True. (* ... *) exact I. Qed.",
 "Print xyz."]
      Output (minimal.json.io.json) after running alectryon --writer json minimal.json:
      [ // A list of processed fragments
  [ // Each fragment is a list of records
    { // Each record has a type, and type-specific fields
      "_type": "sentence",
      "sentence": "Example xyz (H: False): True.",
      "responses": [],
      "goals": [ { "_type": "goal",
                   "name": "2",
                   "conclusion": "True",
                   "hypotheses": [ { "_type": "hypothesis",
                                     "name": "H",
                                     "body": null,
                                     "type": "False" } ] } ] },
    {"_type": "text", "string": " (* ... *) "},
    {"_type": "sentence", "sentence": "exact I.", "responses": [], "goals": []},
    {"_type": "text", "string": " "},
    {"_type": "sentence", "sentence": "Qed.", "responses": [], "goals": []} ],
  [ // This is the second fragment
    { "_type": "sentence",
      "sentence": "Print xyz.",
      "responses": ["xyz = fun _ : False => I\n     : False -> True"],
      "goals": [] } ] ]

  • The exit code produced by Alectryon indicates whether the conversion succeeded: 0 for success, 1 for a generic error, and 10 + the level of the most severe Docutils error if using a Docutils-based pipeline (hence 10 is debug, 11 is info, 12 is warning, 13 is error, and 14 is severe error). Docutils errors at levels below exit_status_level (default: 3) do not affect the exit code, so level 10, 11, and 12 are not used by default.

As a library

Use alectryon.serapi.annotate(chunks: List[str]), which returns an object with the same structure as the JSON above, but using objects instead of records with a _type field:

>>> from alectryon.serapi import annotate
>>> annotate(["Example xyz (H: False): True. (* ... *) exact I. Qed.", "Check xyz."])
[# A list of processed fragments
 [# Each fragment is a list of records (each an instance of a namedtuple)
  Sentence(contents='Example xyz (H: False): True.',
           messages=[],
           goals=[Goal(name=None,
                       conclusion='True',
                       hypotheses=[Hypothesis(names=['H'],
                                              body=None,
                                              type='False')])]),
  Text(contents=' (* ... *) '),
  Sentence(contents='exact I.', messages=[], goals=[]),
  Text(contents=' '),
  Sentence(contents='Qed.', messages=[], goals=[])],
 [# This is the second fragment
  Sentence(contents='Check xyz.',
           messages=[Message(contents='xyz\n     : False -> True')],
           goals=[])]]

The results of annotate can be fed to alectryon.html.HtmlGenerator(highlighter).gen() to generate HTML (with CSS classes defined in alectryon.css). Pass highlighter=alectryon.pygments.highlight_html to use Pygments, or any other function from strings to dominate tags to use a custom syntax highlighter.

As a docutils or Sphinx module

With blogs (Pelican, Nikola, Hugo, etc.)

Include the following code in your configuration file to setup Alectryon's docutils extensions:

import alectryon.docutils
alectryon.docutils.setup()

This snippet registers a .. coq:: directive, which feeds its contents to Alectryon and displays the resulting responses and goals interleaved with the input and a :coq: role for highlighting inline Coq code. It also replaces the default Pygments highlighter for Coq with Alectryon's improved one, and sets :coq: as the default role. See help(alectryon.docutils) for more information.

To ensure that Coq blocks render properly, you'll need to tell your blogging platform to include alectryon.css. Using a git submodule or vendoring a copy of Alectryon is an easy way to ensure that this stylesheet is accessible to your blogging software. Alternatively, you can use alectryon.cli.copy_assets. Assets are stored in alectryon.html.ASSETS.PATH; their names are in alectryon.html.ASSETS.CSS and alectryon.html.ASSETS.JS.

By default, Alectryon's docutils module will raise warnings for lines over 72 characters. You can change the threshold or silence the warnings by adjusting alectryon.docutils.LONG_LINE_THRESHOLD. With Pelican, use the following snippet to make warnings non-fatal:

DOCUTILS_SETTINGS = {
    'halt_level': 3, # Error
    'warning_stream': None # stderr
}

I test regularly with Pelican; other systems will likely need minimal adjustments.

With Sphinx

For Sphinx, add the following to your conf.py file:

extensions = ["alectryon.sphinx"]

If left unset in your config file, the default role (the one you get with single backticks) will be set to :coq:. To get syntax highlighting for inline snippets, create a docutils.conf file with the following contents along your conf.py file (see below for details):

[restructuredtext parser]
syntax_highlight = short

Setting options

Various settings are exposed as global constants in the docutils module:

  • alectryon.docutils.LONG_LINE_THRESHOLD (same as --long-line-threshold)
  • alectryon.docutils.CACHE_DIRECTORY (same as --cache-directory)
  • alectryon.docutils.CACHE_COMPRESSION (same as --cache-compression)
  • alectryon.docutils.HTML_MINIFICATION (same as --html-minification)
  • alectryon.docutils.AlectryonTransform.SERTOP_ARGS (same as --sertop-arg)

Controlling output

The .. coq:: directive takes a list of space-separated flags to control the way its contents are displayed:

  • One option controls whether output is folded (fold) or unfolded (unfold). When output is folded, users can reveal the output corresponding to each input line selectively.
  • Multiple options control what is included in the output. - in: Include input sentences (no-in: hide them) - goals: Include goals (no-goals: hide them) - messages: Include messages (no-messages: hide them) - hyps: Include hypotheses (no-hyps: hide them) - out: Include goals and messages (no-out: hide them) - all: Include input, goals, and messages (none: hide them) - fails (for sentences expected to throw an error): Strip the Fail keyword from the input and remove the The command has indeed failed with message: prefix in the output. (succeeds: leave input and output as-is)

The default is all fold, meaning that all output is available, and starts folded. The exact semantics depend on the polarity of the first inclusion option encountered: x y z means the same as none x y z, i.e. include x, y, z, and nothing else; no-x no-y means all no-x no-y, i.e. include everything except x and y.

These annotations can also be added to individual Coq sentences (⚠ sentences, not lines), using special comments of the form (* .flag₁ … .flagₙ *) (a list of flags each prefixed with a .):

.. coq::

   Require Coq.Arith. (* .none *)             ← Executed but hidden
   Goal True. (* .unfold *)                   ← Goal unfolded
     Fail exact 1. (* .in .messages .fails *) ← Goal omitted
     Fail fail. (* .messages .fails *)        ← Error message shown, input hidden

More precise inclusion/exclusion is possible using the marker-placement mini-language described below. For example:

-.h(Inhabited)
Hide all hypotheses that mention Inhabited
-.g#2.h#IHn
Hide hypothesis IHn in goal 2.
-.g#2.h#*
Hide all hypotheses of goal 2.
-.h#* .h#IHn
Show only hypothesis IHn
-.g#* .g#1 .g#3 .g{False}
Show only goals 1, 3, and any goal whose conclusion is False.

Finally, you can use a [lang]=… annotation to chose which Pygments lexer to use to render part of a goal:

.msg[lang]=haskell
Highlight the bodies of all messages produced by this sentence using the Haskell lexer.

These last two features are experimental; the syntax might change.

Referring to subparts of a proof (the marker-placement mini-language)

Each object in a proof (sentences, goals, messages, hypotheses, conclusions) can be referred to by giving a path that leads to it, written in CSS-inspired notation. This makes it possible to selectively show, hide, or link to parts of the proof state.

In the example below, the markers [α], [β], and [γ] correspond to the paths listed below:

Goal ∀ m n, m + n = n + m. [α]
  induction m; intros.
  - (* Base case *)
    【 n: ℕ ⊢ 0 + n = n + 0 [β] 】
    apply plus_n_O.
  - (* Induction *)
    【 m, n: ℕ; IHm: ∀ n: ℕ, m + n = n + m [γ]
       ⊢ S m + n = n + S m 】

  • [α]

    .s(Goal ∀)

    Search for a sentence (.s(…)) by matching its contents.

  • [β]

    .s(Base case).ccl

    Search for a sentence (.s(…)) matching Base case, then match the conclusion (.ccl) of its first goal.

  • [γ]

    .s(Induction).h#IHm

    Search for a sentence (.s(…)) matching Induction, then match the hypothesis IHm by name (.h#…) in the first goal.

    .s(Induction).g#1.h(m + n = n + m)

    Search for a sentence (.s(…)) matching Induction, select its first goal by number (.g#…), match the hypothesis IHm by searching for its contents (.h(…)).

The full architecture of a path is shown below for reference:

.io#name                        ex: .io#intro
  A block of code whose name matches name.
(.io is optional and defaults to the most recent code block.)

    .s(pattern)                  ex: .s(Goal True)
      Any sentence matching pattern.
    .s{pattern}                  ex: .s{forall*m*n*,}
      Any sentence that completely matches pattern.

       .in
         The input part of the sentence.

       .msg
         Any message
       .msg(str)                 ex: .msg(Closed under global context)
         Any message whose text includes str.
       .msg{pattern}             ex: .msg{*[*syntax*]*}
         Any message whose complete text matches pattern.

       .g#id                     ex: .g#1
         Goal number id.
       .g#name                   ex: .g#base_case
         The goal named name (documentation).
       .g(str)                   ex: .g(True)
         Any goal whose conclusion includes str.
       .g{pattern}               ex: .g{* ++ * ++ * = *}
         Any goal whose complete conclusion matches pattern.
       (.g is optional and defaults to #1.)

           .ccl | .name
             The conclusion or name of the goal.

           .h#name               ex: .h#IHn
              The hypothesis named name.
           .h(str)               ex: .h(Permutation)
              Any hypothesis whose body or type includes str.
           .h{pattern}           ex: .h{nat}
              Any hypothesis whose complete body or type matches pattern.

               .type | .body | .name
                 The type or body or name of the hypothesis.

Plain search patterns (delimited by (…)) are matched literally, anywhere in the term. Other patterns ({…} patterns and #… names) use fnmatch-style matching (? matches any character; * matches any sequence of characters; and [] matches a range of characters), and must match the whole term. Hence:

  • To match hypothesis H1 but not H10 nor IH1, use .h#H1.
  • To match hypotheses of type nat, but not of type list nat or nat -> nat, use .h{nat}
  • To match hypotheses whole type or body includes Permutation anywhere, use .h(Permutation) or .h{*Permutation*}.
  • Etc.

As long as the search term does not contain special characters (*?[]), a plain search ((…)) is the same as an fnmatch-style search with wildcards on both sides ({*…*}).

Finally, you can attach can attach arbitrary key-value to subparts of a goal matched using the marker-placement mini-language by appending [key]=value after the path. This is useful with custom transforms and with the [lang]=… setting to customize highlighting for a given sentence or message.

This feature is experimental; the syntax might change.

Extra roles and directives

For convenience, Alectryon includes a few extra roles and directives:

Markers and marker references

The :mref: role (short for “marker reference”) can be used to point the reader to a sentence, a goal, or a hypothesis. The argument is a search pattern written in the marker-placement mini-language; Alectryon locates the corresponding object in the input sent to the prover or in the prover's output, inserts a marker at that point, and replaces the reference with a link to that marker.

For example, the [γ] marker in the example above could be inserted using :mref:`.s(Induction).h#IHm` or :mref:`.s(Induction).g#1.h(m + n = n + m)`.

By default markers refer to the most recent .. coq:: block, but other blocks can be targeted by name by prepending .io#name to the argument of :mref:.

Markers can be customized by setting the :counter-style: option on a custom role derived from :mref:; for example, to use Devanagari numerals:

.. role:: dref(mref)
   :counter-style: ० १ २ ३ ४ ५ ६ ७ ८ ९

More details and examples are given in recipes/references.rst.

This feature is experimental: the syntax might change.

Quoted references to goal fragments

The :mquote: role is similar to :mref:, but it inserts a copy of the target instead of a link to it. Targets may only be hypotheses, goal conclusions, or goal or hypothesis names.

For example, using :mquote:`.s(Induction).h#IHm.type` in the example above would print the type of IHm, ∀ n: ℕ, m + n = n + m whereas :mref:`.s(Induction).g#1.h(m + n = n + m).name` would produce only the name of the corresponding hypothesis, IHm.

An .. mquote: directive is also available. It places the quoted elements in a block and preserves indentation and newlines, unlike the :mquote: role (whose output appears inline).

More details and examples are given in recipes/references.rst.

Output assertions

Sometimes it is desirable to check that the prover produced the right output, without displaying that output to the user. In these cases, Alectryon's marker-placement mini-language can serve as a poor lad's unit test. The massert directive takes one argument (a path prefix), and checks that each line of its body is a valid reference to part of a previous goal.

More details and examples are given in recipes/references.rst.

Links to Coq identifiers

:coqid: can be used to link to the documentation or definition of a Coq identifier in an external file. Some examples:

By default, :coqid: only knows how to handle names from Coq's standard library (that is, names starting with Coq., which get translated to links pointing to https://coq.inria.fr/library/). To link to other libraries, you can add entries to alectryon.docutils.COQ_IDENT_DB_URLS, a list of tuples containing a prefix and a templated URL. The URL can refer to $modpath, the part before the last # or . in the fully qualified name, and $ident, the part after the last # or .. Here is an example:

("My.Lib", "https://your-url.com/$modpath.html#$ident")

Alternatively, you can inherit from :coqid: to define new roles. The following defines a new :mylib: role, which assumes that its target is part of My.Lib:

.. role:: mylib(coqid)
   :url: https://your-url.com/My.Lib.$modpath.html#$ident

Caching

The alectryon.json module has facilities to cache the prover's output. Caching has multiple benefits:

  1. Recompiling documents with unchanged code is much faster, since Coq snippets do not have to be re-evaluated.
  2. Deploying a website or recompiling a book does not require setting up a complete Coq development environment.
  3. Changes in output can be inspected by comparing cache files. Caches contain just as much information as needed to recreate input/output listings, so they can be checked-in into source control, making it easy to assess whether a Coq update meaningfully affects a document (it's easy to miss breakage or subtle changes in output otherwise, as when using the copy-paste approach or even Alectryon without caching).

To enable caching on the command line, chose a directory and pass it to --cache-directory. Alectryon will record inputs and outputs in individual JSON files (one .cache file per source file) in subdirectories of that folder. You may pass the directory containing your source files if you'd like to store caches alongside inputs.

From Python, set alectryon.docutils.CACHE_DIRECTORY to enable caching. For example, to store cache files alongside sources in Pelican, use the following code:

import alectryon.docutils
alectryon.docutils.CACHE_DIRECTORY = "content"

With a custom driver

For advanced usage, or to customize Alectryon's command-line interface, you can use a custom driver. Create a new Python file, and add the following to it:

from alectryon import cli
… Any extension code here
cli.main()

Extensions might include, registering additional docutils directives or roles with docutils.directives.register_directive and docutils.roles.register_canonical_role, adding custom syntax highlighting for project-specific tokens using alectryon.pygments.add_tokens, or even tweaking the operation of the Coq lexer in alectryon.pygments_lexer, or monkey-patching parts of Alectryon's docutils module.

See recipes/alectryon_custom_driver.py for a concrete example.

Other proof assistants

Lean 4

Alectryon has support for Lean 4. LeanInk (LeanInk) is required to use Alectryon with Lean 4 files. HTML and LaTeX output is supported from plain .lean source files and from .rst files. The reStructuredText directive for Lean 4 is .. lean4::, for Markdown/MyST files it is {lean4}. The literate delimiter is /-!:

  • Include Lean 4 code in reStructuredText files like this:

    Some reST prose.

.. lean4::

   … some Lean 4 code

  • Include reStructuredText prose in Lean 4 files like this:

    … some Lean 4 code

/-!
Some reST prose.
-/

See recipes/plain-lean4.lean, recipes/lean4-tactics.rst, recipes/lean4-tactics-myst.md and recipes/literate-lean4.lean for examples.

Lean 4 support was contributed by Niklas Bülow (@insightmind).

Lean 3

Alectryon has preliminary support for Lean 3.

Recording Lean's output and generating HTML or LaTeX is supported, from plain .lean files and from .rst files using the .. lean3:: directive (as well as Markdown/MyST files using the {lean3} directive). Language-agnostic features like caching work. The literate delimiter is /-!; in other words, you may write:

  • Include Lean 3 code in reStructuredText files like this:

    Some reST prose.

.. lean3::

   … some Lean 3 code

  • Include reStructuredText prose in Lean 3 files like this:

    … some Lean 3 code

/-!
Some reST prose.
-/

See recipes/plain-lean3.lean and recipes/lean3-tutorial.rst for examples.

The following features are missing:

  • Concurrent processing of documents. See the long comment above USE_THREADING in class Lean3 of alectryon/lean3.py.
  • Support for literate Lean documents in Emacs/alectryon-mode.

Support for quoting snippets and displaying or hiding sentences is partial.

For a more detailed TODO list, see the header of alectryon/lean3.py.

Polyglot documents

reStructuredText and Markdown documents compiled with Alectryon may combine all supported languages. Code from each language is executed separately. See recipes/polyglot.rst for an example.

Tips

Prettification

Programming fonts with ligatures are a good way to display prettified symbols without resorting to complex hacks. Good candidates include Fira Code and Iosevka (with the latter, add .alectryon-io { font-feature-settings: 'XV00' 1; } to your CSS to pick Coq-specific ligatures).

Passing arguments to SerAPI

When using the command line interface, you can use the -I, -Q, -R and --sertop-arg flags to specify custom SerAPI arguments, like this:

alectryon -R . Lib --sertop-arg=--async-workers=4

When compiling reStructuredText documents, you can add custom SerAPI arguments in a docinfo section at the beginning of your document, like this:

:alectryon/serapi/args: -R . Lib -I mldir

To set SerAPI's arguments for all input files, modify AlectryonTransform.DRIVER_ARGS["sertop"] in alectryon.docutils. Here's an example that you could use in a Sphinx config file:

from alectryon.docutils import AlectryonTransform
AlectryonTransform.DRIVER_ARGS["sertop"] = ["-Q", "/coq/source/path/,LibraryName"]

Note that the syntax of DRIVER_ARGS["sertop"] is the one of sertop, not the one of coqc (rocq-archive/coq-serapi#215).

Adding custom keywords

You can use alectryon.pygments.add_tokens to specify additional highlighting rules, such as custom tactic names. See help(alectryon.pygments.add_tokens) for more details.

When compiling reStructuredText documents, you can add per-document highlighting rules to the docinfo section at the beginning of your document, like this:

:alectryon/pygments/coq/tacn: intuition_eauto simplify invert
:alectryon/pygments/coq/tacn-solve: map_tauto solve_eq

Interactivity

Most features in Alectryon's HTML output do not require JavaScript, but extra functionality (including keyboard navigation) can be added by loading assets/alectryon.js (this is done by default).

Scripts needed to unminify documents produced with --html-minification (see below) are bundled into the generated HTML and do not need to be loaded separately.

Authoring support

The etc/elisp folder of this directory includes an Emacs mode, alectryon.el, which makes it easy to switch between the Coq and reStructuredText views of a document.

Docutils configuration

You can set Docutils settings for your single-page reST or Coq+reST documents using a docutils.conf file. See the documentation or the example in recipes/. For example, the following changes latex-preamble for the XeTeX backend to custom fonts:

[xetex writer]
latex-preamble:
  \setmainfont{Linux Libertine O}
  \setsansfont{Linux Biolinum O}
  \setmonofont[Scale=MatchLowercase]{Fira Code}

You can also use the DOCUTILSCONFIG environment variable to force alectryon to use a specific configuration file.

Reducing page and cache sizes (experimental)

Proofs with many repeated subgoals can generate very large HTML files and large caches. In general, these files compress very well — especially with XZ and Brotli (often over 99%), less so with GZip (often over 95%). But if you want to save space at rest, the following options may help:

  • --html-minification: Replace repeated goals and hypotheses in the generated HTML with back-references and use more succinct markup. Minimal Javascript is included in the generated page to resolve references and restore full interactivity. Typical results:

    4.4M List.html          24.8M Ranalysis3.html
1.4M List.min.html       452K Ranalysis3.min.html

  • --cache-compression: Compress caches (the default is to use XZ compression). Typical results:

    3.2M List.v.cache       21M Ranalysis3.v.cache
 66K List.v.cache.xz    25K Ranalysis3.v.cache.xz

From Python, use alectryon.docutils.HTML_MINIFICATION = True and alectryon.docutils.CACHE_COMPRESSION = "xz" to enable minification and cache compression.

A minification algorithm for JSON is implemented in json.py but not exposed on the command line.

Diffing compressed caches

Compressed caches kept in a Git repository can be inspected by automatically decompressing them before computing diffs:

# In $GIT_DIR/config or $HOME/.gitconfig:
[diff "xz"]
  binary = true
  textconv = xzcat

# In .gitattributes:
*.cache.xz diff=xz

Building without SerAPI

Alectryon can compile documents using coqc. Sentences be split correctly, but goals and messages will not be collected, and error reporting will be less precise. To use this feature, pass --coq-driver=coqc_time to Alectryon.

Building without Alectryon

The alectryon.minimal Python module provides trivial shims for Alectryon's roles and directives, allowing you continue compiling your documents even if support for Alectryon stops in the future.

Including custom JS or CSS in Alectryon's output

For single-page documents, you can use a .. raw:: directive:

.. raw:: html

   <script src="https://d3js.org/d3.v5.min.js" charset="utf-8"></script>
   <script src="https://dagrejs.github.io/project/dagre-d3/latest/dagre-d3.js"></script>

   <link rel="stylesheet" href="rbt.css">
   <script type="text/javascript" src="rbt.js"></script>

For documents with more pages, you can either move the .. raw part to a separate file and .. include it, or you can use a custom driver: create a new file driver.py and use the following:

import alectryon.html
import alectryon.cli

alectryon.html.ADDITIONAL_HEADS.append('<link rel="stylesheet" href="…" />')
alectryon.cli.main()

But for large collections of related documents, it's likely better to use Sphinx (or some other similar engine). In that case, you can use Sphinx' built-in support for additional JS and CSS: app.add_js_file(js) and app.add_css_file(css).

Special case: MathJax

MathJax is a JavaScript library for rendering LaTeX math within webpages. Properly configuring it can be a bit tricky.

  • If you just want to include math in reStructuredText or Markdown documents, docutils will generally do the right thing: it will generate code to load MathJaX from a CDN if you use the :math: role, and it leave that code out if you don't.
  • If you want to render parts of your Coq code using MathJaX, things are trickier. You need to identify which text to render as math by wrapping it into \( … \) markers; then add the mathjax_process class to the corresponding document nodes to force processing (otherwise MathJax ignores the contents of Alectryon's <pre> blocks); then trigger a recomputation. See ./recipes/mathjax.rst for an example and a more detailed discussion.

Suggested projects / TODOs

I do not work on the following tasks, but it would be very useful to complete them:

  • Add support for converting to and from Markdown/MyST instead of reST. This requires (1) changing literate.py to support reading and writing myst (a simple state machine); (2) adjusting cli.py to expose the new conversion functions; and (3) modifying etc/elisp/alectryon.el to make it convenient to switch back and forth.
  • Upstream Alectryon's Coq highlighter for Pygments (it's an almost-complete rewrite of the original one).
  • Add support for prettification in Pygments (display forall as ∀, etc.). This require (1) Adding a pygments filter for prettification and (2) special-casing the rendering of prettified symbols somehow, so that copy-pasting them produces the original, unprettified rendering.
  • Add support for diffing (displaying only changed hypotheses). See https://github.com/ejgallego/coq-serapi/issues/251
  • Add support for mquote-ing full goals and sentences. This requires revamping the CSS (right now it assumes a specific nesting order of classes, and subparts of a proof state except the currently supported ones do not display correctly).
  • Add support for quoting parts of another file, including its proof states: (1) design a mini-language to specify where to start and end, either in term of which definitions to select, or in terms of strings of text or regular expressions, or a combination (“definition of x within module A” or “from induction … to solve [eauto] in proof of foo”); (2) load documents that these directives refer to and embed the corresponding parts, compiling (with caching) as needed.

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